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					                                         The Pursuit of Customer Profitability




Emagine International
Global Benchmark Diagnostic


Best Practice Churn Management
Strategies for Pre & Pospaid Customers




                    The Global Mobile Industry Bechmark
Churn Management Strategy


Table of Contents

Table of Contents..................................................................................................1
Table of Figures ....................................................................................................5
Executive Summary ..............................................................................................9
Disclaimer ...........................................................................................................10
       Intellectual property rights ........................................................................10
       Abuse of confidentiality ............................................................................10
       Disclaimer ................................................................................................10
1 Introduction ..................................................................................................11
  1.1     About Emagine International ................................................................11
  1.2     About this report ...................................................................................12
  1.3     Document Purpose ...............................................................................12
  1.4     Confidentiality .......................................................................................12
  1.5     Operator Codes ....................................................................................13
2 Research Methodology................................................................................14
  2.1     Overview...............................................................................................14
  2.2     Methodology .........................................................................................14
    2.2.1      Purchasing Power Parity (PPP) Conversion Method.....................14
    2.2.2      Market Competitiveness Index ......................................................14
    2.2.3      Best Practice Defined ....................................................................15
    2.2.4      Customer Lifetime Net Present Value (NPV) Defined ...................17
    2.2.5      Definitions Used in this study ........................................................18
  2.3     Participant Selection and Recruitment..................................................21
  2.4     Questionnaire Development .................................................................21
  2.5     Data Collection .....................................................................................21
  2.6     Data Analysis........................................................................................22
  2.7     Case Studies ........................................................................................22
3 Churn Management Strategies ....................................................................23
  3.1     Overview...............................................................................................23
  3.2     Executive Highlights .............................................................................23
  3.3     Introduction...........................................................................................24
       3.3.1 As markets become increasingly competitive operators get
               Postpaid churn under control… for a while...................................24
       3.3.2 The degree of market competitiveness also impacts on the level of
               Prepaid churn in the same way, although not to the same degree 25
  3.4     Detailed Findings ..................................................................................27
    3.4.1      Churn management strategy rankings...........................................27
       3.4.1.1 Operators ranked comprehensive customer information, reactive
                   save and churn prediction as the top three important retention
                   strategies ...................................................................................27
    3.4.2      Emagine Priority Matrix of Churn Management Strategies............27
    3.4.3      Churn management strategies Impact versus cost complexity......28
  3.5     Churn Management Strategies - Best Practice Benchmarks................29
  3.6     High impact churn management strategies ..........................................30


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   3.6.1    Obtain Comprehensive Customer Information ..............................30
     3.6.1.1 Operators have far more knowledge of their Postpaid base than
                their Prepaid base......................................................................30
   3.6.2    Implement Reactive Customer Save Process ...............................33
   3.6.3    All operators in the study offered at least a basic customer save
            function with some offers. 25% of operators offer a real time value
            based, fully automated customer save process with extensive offers
             ......................................................................................................33
   3.6.4    Though only 50% of operators in the study have a customer save
            function for Prepaid customers, 44% offer at least a basic function
            with some save offers....................................................................34
   3.6.5    Best practice save rates for Prepaid are 19%, and Postpaid 65% of
            those customers contacted............................................................34
   3.6.6    81% of operators only consider high value Postpaid customers for
            targeting by customer save teams while 19% consider all Postpaid
            customers......................................................................................35
   3.6.7    50% of churning customers are contacted for Postpaid while on
            average only 17% of Prepaid churning customers are contacted by
            customer save teams ....................................................................36
   3.6.8    On average 41% of contacted Postpaid customers are saved by
            customer save teams of which 58% are still with the operator six
            months later...................................................................................37
   3.6.9    Most highly effective save offers for Postpaid customers are
            handset upgrades, contracts/recontracting offers and air time offers
             ......................................................................................................38
   3.6.10 Handset upgrades followed by SIM lock and air time offers are
            proving the most effect customer save offers for Prepaid customer
            save...............................................................................................39
     3.6.10.1 Case Study: Prepaid handset upgrade program launched with
                   great success .........................................................................40
   3.6.11 Use Churn Prediction in Operations ..............................................41
   3.6.12 83% of medium to high MCI operators have a churn prediction
            solution ..........................................................................................41
   3.6.13 68% of operators are churn propensity scoring Postpaid customers
            at least monthly .............................................................................42
   3.6.14 75% of operators are yet to use churn prediction campaigns for
            Prepaid customers.........................................................................43
     3.6.14.1 Case Study: European operator uses simple and effective
                   Prepaid churn prediction model.............................................44
   3.6.15 Best practice churn prediction scoring scored 70% of churning
            customers in the top 2% of churned customers.............................45
   3.6.16 Conduct Proactive Campaigns ......................................................47
     3.6.16.1 Majority of operators have a campaign test team for Prepaid
                   and Postpaid marketing strategies .........................................47




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      3.6.16.2     Postpaid operators are becoming more sophisticated in their
                   use of marketing tools for campaign management but still lag
                   behind for Prepaid campaigns................................................48
     3.6.16.3 Most operators test between 0-10 campaigns per month for
                   both pre and Postpaid ............................................................49
     3.6.16.4 The majority of campaigns tested are deployed .....................50
     3.6.16.5 Most operators conduct their campaign management activities
                   in-house .................................................................................51
   3.6.17 Implement tariff plan optimisation ..................................................53
   3.6.18 Manager Customer Interaction by Segment ..................................56
   3.6.19 Over 80% of operators use customer value information in
            differentiating customer service and offers made to high value
            customers for Postpaid..................................................................56
   3.6.20 For Prepaid, no operators in low MCI markets in the study are
            actually using customer value information in customer interactions
             ......................................................................................................57
   3.6.21 56% of operators are using churn prediction scores as a basis for
            making marketing offers to Postpaid customers............................58
   3.6.22 The more competitive the market, the more likely that churn
            prediction scoring on Postpaid customers is used.........................59
   3.6.23 69% of operators send more frequent and expensive marketing
            communications to high value customers......................................60
   3.6.24 92% of operators in highly competitive markets use customer value
            information to differentiate marketing communications to Postpaid
            customers......................................................................................61
   3.6.25 69% of operators use churn propensity information to differentiate
            marketing communications to high value Postpaid customers ......62
   3.6.26 A much higher proportion of operators in medium to highly
            competitive markets are using churn propensity scoring to
            differentiate marketing communications to Postpaid customers with
            83% vs. 25% respectively..............................................................63
   3.6.27 Only operators in medium to highly competitive markets are using
            churn propensity scoring to differentiate marketing communications
            to Prepaid customers.....................................................................64
   3.6.28 No operator in the study differentiates network access on call costs
             ......................................................................................................65
   3.6.29 Over 93% of operators make customer value segmentation data
            available to marketing, customer service and customer save .......66
   3.6.30 Use Customer Contracts (Postpaid) or SIM Lock (Prepaid) ..........67
     3.6.30.1 75% of operators use contracts for Postpaid, and 56% use SIM
                   lock for Prepaid. .....................................................................67
   3.6.31 Implement Re-Subsidisation and/or Handset Upgrade Programs .68
     3.6.31.1 Handset subsidies are much greater for Postpaid than Prepaid
                   customers...............................................................................68
     Emagine point of view ..............................................................................68



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   3.6.32 Implement Operational Customer Segmentation...........................69
     3.6.32.1 Most Prepaid operators are not yet conducting customer value
                 based segmentation ...............................................................69
     3.6.32.2 80% of high MCI operators are running customer value
     segmentation methods with 58% using average revenue/rate plan based
     segmentation followed by 50% using tiered Gold/Silver/Bronze forms of
     segmentation............................................................................................70
   3.6.33 Implement Recontracting Offers....................................................71
     3.6.33.1 Churn significantly reduces when operators recontract their
                 customers...............................................................................71
     3.6.33.2 37% of operators have achieved or exceeded their objectives
                 for re-contracting campaigns, whilst a further 25% are
                 achieving partial objectives. ...................................................72
   3.6.34 Implement Loyalty Programs.........................................................73
     3.6.34.1 Far fewer operators offer rewards for Prepaid customers than
                 for Postpaid ............................................................................73
   3.6.35 Case Study – Loyalty Programs ....................................................74
   3.6.36 Recharge Campaigns (Prepaid) ....................................................78
     3.6.36.1 37% of operators have achieved or exceeded their objectives
                 for Prepaid recharge campaigns, whilst a further 25% are
                 achieving partial objectives ....................................................78
   3.6.37 Migration Strategies for Prepaid and Postpaid ..............................79
     3.6.37.1 Only 6% of operators reported that a migration strategy for
                 Prepaid to Postpaid had been successfully implemented and
                 met or exceeded their core objectives for such a strategy .....79
   3.6.38 56% of Operators have no plans for implementing a migration
            strategy for Postpaid to Prepaid ....................................................80
   3.6.39 Offers – What Offers Actually Work to Reduce Customer Churn? 81
     3.6.39.1 Retention offers that reduce the cost to the customer are the
                 most effective at reducing churn.............................................81
4 Future of CRM .............................................................................................82
 4.1 Most medium to high MCI operators are expecting churn will not change
     substantially within 12 months..................................................................82
   4.1.1    CRM Programmes of the future.....................................................83
   4.1.2    Using existing channels to service customers ...............................84
     4.1.2.1 Direct Channels .........................................................................84
     4.1.2.2 Indirect channels........................................................................84
     4.1.2.3 Operators website......................................................................85
     4.1.2.4 Mobile Internet ...........................................................................85




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Table of Figures

Figure 1.1    Emagine International – Overview                            10

Figure 2.1    Market Competitiveness                                      15

Figure 2.2    Average customer lifetime NPV                               16

Figure 2.3    Market Competitiveness Index (MCI)                          17

Figure 3.1    Postpaid annual churn and Postpaid customer lifetime NPV
              by market competitiveness                                   24

Figure 3.2    Prepaid annual churn and Prepaid customer lifetime NPV
              by market competitiveness                                   25

Figure 3.3     Operators ranking of churn management strategies in order of
              importance                                                 27

Figure 3.4    Impact versus cost complexity – churn management strategies
                                                                       28

Figure 3.5    Summary of best practice churn management strategies
                                                                          29

Figure 3.6    Percentage of operators who have certain information re their
              customer base - Postpaid                                    30

Figure 3.7    Percentage of operators who have certain information re their
              customer base – Prepaid                                     31

Figure 3.8    Reactive save status of operators – Postpaid                33

Figure 3.9    Reactive save status of operators – Prepaid                 34

Figure 3.10   Best practice and Average customer save performance
              indicators                                                  34

Figure 3.11   Percentage breakdown of what customers operators consider
              for save - Postpaid versus Prepaid                      35

Figure 3.12   Comparison of average percentage of potential churners
              targeted against average percentage of churned customers
              contacted – Postpaid versus Prepaid                      36

Figure 3.13   Comparison of average retention rate of those contacted
              against average retention rate of those with operator 6 months
              later – Postpaid versus Prepaid                              37

Figure 3.14   Percentage breakdown of customer save offer effectiveness
              – Postpaid                                                38



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Figure 3.15   Percentage breakdown of customer save offer effectiveness
              – Prepaid                                                 39

Figure 3.16   Percentage breakdown of whether operators have a
              churn prediction solution in place – split by market
              competitiveness                                                 41

Figure 3.17   Churn prediction status of operators - Postpaid                 42

Figure 3.18   Churn prediction status of operators - Prepaid                  43

Figure 3.19   “Lift curve” achieved by some operators and the overall
              average - Postpaid                                              45

Figure 3.20   Percentage of operators who have a proactive campaign test
              team – Postpaid versus Prepaid                          47

Figure 3.21   Proactive campaign management status of operators
              - Postpaid                                                      48

Figure 3.22   Proactive campaign management status of operators
              - Prepaid                                                       48

Figure 3.23   Percentage breakdown of the average number of campaigns
              tested per month – Postpaid versus Prepaid            49

Figure 3.24   Average percentage of campaigns actually deployed per
              month – Postpaid versus Prepaid                                 50

Figure 3.25   Percentage breakdown of whether operators are conducting
               their proactive activities in-house versus outsourced
              - Postpaid                                              51

Figure 3.26   Percentage breakdown of whether operators are conducting
              their proactive activities in-house versus outsourced – Prepaid
                                                                            52

Figure 3.27   Percentage breakdown of the use of tariff plan optimisation by
              operators and their effectiveness                            53

Figure 3.28   Churn reduction required to justify decrease in ARPU due to
              rate plan optimisation (ROI 100% in 12 months)              54

Figure 3.29   How operators are using customer value segmentation
               information in their customer interactions – Postpaid versus
              Prepaid                                                         56

Figure 3.30   How operators are using customer value segmentation
              information in their customer interactions – Prepaid split by
              market competitiveness                                          57




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Figure 3.31   How operators are using churn prediction information in their
              customer interactions – Postpaid versus Prepaid               58

Figure 3.32   How operators are using churn prediction information in
              their customer interactions – Postpaid and split by market
              competitiveness                                              59

Figure 3.33   How operators are using customer value information to
              differentiate marketing communications – Postpaid versus
              Prepaid                                                      60

Figure 3.34   How operators are using customer value information to
              differentiate marketing communications – Postpaid and
              split by market competitiveness                              61

Figure 3.35   How operators are using churn propensity information to
              differentiate marketing communications – Postpaid versus
              Prepaid                                                      62

Figure 3.36   How operators are using churn propensity information to
              differentiate marketing communications – Postpaid and split
              by market competitiveness                                   63

Figure 3.37   How operators are using churn propensity information to
              differentiate marketing communications – Prepaid and split
              market competitiveness                                     64

Figure 3.38   Percentage breakdown of whether operators are differentiating
              network access priority based on whether the call is a free
              or paid call                                                65

Figure 3.39   Percentage breakdown of the divisions operators are making
              customer value segmentation information available to      66

Figure 3.40   Percentage breakdown of the use of customer contracts for
              Postpaid handsets and the use of SIM locks for Prepaid
              handsets                                                  67

Figure 3.41   Average handset subsidies for acquisition versus retention
              – split Postpaid versus Prepaid                              68

Figure 3.42   Percentage breakdown of the use of customer value
              segmentation methods – Postpaid versus Prepaid               69

Figure 3.43   Percentage breakdown of the use of customer value
              segmentation methods for both Postpaid versus Prepaid
              – split by market competitiveness                            70

Figure 3.44   Average off contract versus on contract and recontract
              churn comparison within the medium market
              competitiveness stage                                        71


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Figure 3.45   Percentage breakdown of the use of recontracting offers by
              operators and their effectiveness                          72

Figure 3.46   Percentage breakdown of rewards offered by operators in their
              Postpaid and Prepaid loyalty programs                     73

Figure 3.47   Percentage breakdown of the use of recharge campaigns
              – Prepaid and their effectiveness                          78

Figure 3.48   Percentage breakdown of the use of migration strategies
              – Prepaid to Postpaid and their effectiveness              79

Figure 3.49   Percentage breakdown of the use of migration strategies
              – Postpaid to Prepaid and their effectiveness              80

Figure 3.50   Percentage breakdown of the effectiveness of retention offers
                                                                          81

Figure 4.1    Comparison of current total monthly churn rate versus forecasted
              churn rate in 12 months time                                82




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Executive Summary

This report identifies the strategies that Best Practice Operators use to combat
churn for both Prepaid and Postpaid customers. Specifically it provides an
assessment of the impact versus cost/complexity of the full range of churn
management strategies employed by operators and best practice benchmarks
achieved.

The report shows that Operators can achieve quick wins in the battle against
churn by obtaining comprehensive customer information and applying this
information to dedicated churn prediction and customer save programs.

The report also looks at what type of offers are actually working to reduce churn.
It shows that the most effective retention offers are those that relate to the core
business of the operator and most importantly, reduce the cost to the customer.
The most effective examples include free airtime, handset upgrades,
contracts/re-contracting and rate plan optimisation.

The report also looks at some of how to manage churn in the future as the
market becomes saturated and the Operator’s business changes with the
advent of data services.

The report has over 50 charts and 3 case studies included.




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Disclaimer

Intellectual property rights
The findings, views and opinions presented herein are those of Emagine
International and cannot be reprinted, copied or re-transmitted in any form
without the express permission of Emagine International.

Abuse of confidentiality
Emagine International has entered into confidentiality agreements with all
participants regarding the handling of information supplied to Emagine
International as part of the study and considered confidential to each
participant.

Emagine International is bound by those confidentiality agreements, which in
summary mean, that at no time, shall Emagine International nor any of its
representatives or agents;

   •   Specifically identify which operators have participated in this study
   •   Attribute any material presented in this report directly to a particular
       operator excluding to a participant that which has been provided by the
       participant directly

Operator names are used in Case Studies that appear in the Customer Retention
Handbook, however these operators are not necessarily participants in this study.
Publicly available information has been used for the case studies, which are
intended to provide a practical illustration of a particular Emagine point of view
or specific initiative.

Disclaimer
Emagine International has used its best efforts in preparing this report. All
information presented is directly based on information supplied by participating
operators. In rare situations where quantitative information was not supplied
directly by the participants, public domain information, including website
information or estimates have been used. All participants have had the
opportunity to comment on these estimates and suggest variations where
appropriate. Emagine International can provide no express or implied warranties
with respect to the accuracy of the contents of this report. Emagine International
specifically denies any implied warranties of useability of this report for any
particular purpose and at no time shall be liable for any loss or consequential
damages resulting from actions taken subsequent to this report.




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1      Introduction

    1.1 About Emagine International
    Emagine International’s aim is to enable our telecommunications clients to
    pursue customer profitability leadership.

    Emagine       provides    closed-loop     marketing  solutions  that  enable
    telecommunications operators to pursue customer profitability leadership by
    creating intelligent, value-based customer interaction at each customer touch
    point. We rapidly deploy high-impact churn management and revenue
    stimulation strategies across multiple channels.




    Figure 1.1   Emagine International – Overview

    How Emagine delivers customer profitability leadership…

       •   Emagine’s global benchmark diagnostic provides unique insight and a
           roadmap for high-impact initiatives which actually work to reduce churn
           and stimulate revenue.
       •   Emagine’s Closed-Loop Marketing Suite for Telecommunications is a
           comprehensive modular solution designed to deliver the high-impact
           quick-wins to achieve customer profitability leadership
       •   We     specialise   in    telecommunications       and   deliver  deep
           telecommunications industry experience immediately to your business. We
           bridge the gap in your organisation between marketing strategy,
           technology solutions and operational execution



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   •   Our “ROI driven CRM” implementation methodology ensures that the
       business objectives and results, not the technology, drive the entire
       closed-loop marketing project
   •   We believe in the power of our methodology and solutions - our license
       fees are based on success

For more information on Emagine International see www.Emagine-int.com

1.2 About this report
The Best Practice Churn Management Strategies for Prepaid and Postpaid
Customers report has been prepared based on information gathered from
Emagine International’s International Customer Value Management study. The
study is a global multi-client consulting initiative of Emagine International, that
benchmarks mobile operators best practice performance

This study provides a unique apples-to-apples comparison of best practice
activities between operators, with a valuable mixture of in-depth quantitative
and qualitative measures, practical case studies and Emagine commentary.

Emagine’s study involves in-depth one-on-one interviews with leading cellular
operators from Europe, Asia Pacific and the United States and reports the very
latest benchmarks and developments for both Prepaid and Postpaid cellular
operators.

1.3 Document Purpose
This report is a global best practice benchmark designed to assist mobile
operators to understand and achieve best practice in terms of their churn
management strategies

It has been designed to offer insights into the strategies and programs used by
mobile operators in similarly competitive markets.

This study focuses on identifying current and potential best practice strategies
and programs, then presents how the participant’s operations compare with
these practices.

From this comparison, it is proposed that readers will be able to develop insights
into how their operation should be improved to address the problem of customer
retention and how best to react to or pre-empt changing market conditions.

1.4 Confidentiality
Owing to the highly sensitive nature of the information in this study, Emagine
International is unable to release details either of study participants, or which
operator represents which results. Therefore a code system has been used



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throughout the report to allow individual participants to identify themselves and
how they compare to other operators in the study.

1.5 Operator Codes
Due to the high number of operators in this study, operator codes are listed in
‘alphabetical’ order, (A, B, C etc.) in order of an operator’s increasing market
competitive index.

Many charts that break data up into regional data for Europe, Asia and United
States will stipulate averages for each region accordingly.




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2 Research Methodology

  2.1 Overview
  This section provides an overview of the methodology used in this report,
  including the definitions for common terms. It also outlines the process behind
  participant selection, recruitment, data collection and analysis.

  2.2 Methodology

  2.2.1   Purchasing Power Parity (PPP) Conversion Method

  In order to provide a useful comparison of operators’ efforts in multiple countries
  it was necessary to first convert all financial data into a common currency. Due
  to its dominance in world trade, the United States dollar US$ was chosen as the
  benchmark currency for the study.

  Furthermore, to balance the price levels of local economies and current
  exchange rates on the US$ benchmarks, all figures were adjusted using the atlas
  method of purchasing power parities as published by the World Bank. This
  method provides a more useful benchmark output.

  For more details on purchasing power parities and why they are used, go to:
  www.oecd.org/std/ppp/pppfaq.htm

  2.2.2   Market Competitiveness Index

  To normalise for differences between operators’ local market competitiveness,
  Emagine has developed a Market Competitiveness Index (MCI) based on:

   Market Competitiveness Characteristic         Indicator Used in MCI
   Level of direct competition                   Number of operators in market
   Intensity of competition                      Acquisition costs and handset subsidies
   Intensity of competition                      Average price per minute
   Maturity of the market                        Mobile penetration rate by population
   Regulatory controls on competition            Mobile number portability existence
   Population coverage                           Percentage Population covered


  The Market Competitiveness Index methodology in this study has been adjusted
  again according to the weightings for each variable this year. Ratings are based
  on the operator’s own assessment of the importance and impact of each of the
  variables on market competition.




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                            MARKET
                            COMPETITIVENESS
                            LEVELS
                            Low MCI              20-40%
                            Medium MCI           41-61%
                            High MCI             62% +



Figure 2.1    Market Competitiveness

To retain confidentiality of each operator, the exact calculation of the Market
Competitiveness Index is not provided and is proprietary to Emagine
International Pty Ltd.

2.2.3   Best Practice Defined

Typically, when looking at the area of customer retention for mobile operators,
the analysis focuses almost exclusively on churn rates.

However, if the objective is to maximise the net asset value of the business, then
the most important consideration is the total value of the customer base that is
being retained.

Figure 1.1 represents the critical indicator of the financial health of an operator
as the value of the customers’ lifetime contribution towards profitability
(discounted to today’s dollar terms), measured as customer lifetime net present
value (NPV).




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                            Decaying over
                                 time




     $x margin

                                                     Average lifetime




                                    Tenure
              Average
             customer
          lifetime NPV




Figure 2.2       Average customer lifetime NPV

Accordingly, the key indicator of best practice in this study is determined by the
maximisation of average customer lifetime NPV.

Note that this figure is highly dependent on the churn rate, and therefore churn
remains an important, but not exclusive, benchmark indicator.

In the report much of the data is analysed using the Market Competitiveness
index as the x-axis, thus enabling participants to measure themselves against
operators of similarly competitive markets.

Figure 1.2 illustrates best practice movement for operators – the ideal result is for
an operator to reduce churn (move downwards), increase or maintain NPV (size
of bubble) as their market becomes more competitive (moving right).




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                      (size of bubble indicates customer lifetime NPV)

         60%
Annual
churn
rate     50%


         40%


         30%


         20%

                                                               Best
         10%
                                                              Practice

         0%


               Market Competitiveness

Figure 2.3      Market Competitiveness Index (MCI)

Note that it is indeed possible that markets need not inexorably become more
and more competitive (move right) and hence operators need not assume that
they will continually have a higher and higher MCI.

The inputs to the MCI are based around the variables shown in section 2.2.2,
some of which the operator has the ability to control. With consolidation,
reduction in subsidies, and government regulation, markets may become less
competitive over time.




2.2.4    Customer Lifetime Net Present Value (NPV) Defined

The generally accepted definition of customer lifetime NPV is the total profit
earned per customer over the average customer lifetime.

Different operators may adopt different internal calculations of customer lifetime
NPV. For the purpose of benchmark comparisons, Emagine has applied a
common model across all participants in the study.

It is worthwhile to understand the formula used and its implications.

Customer      lifetime   NPV     =     (-    Acquisition                    cost)       +
((ARPU*Margin)/WACC)*((1(1/(1+WACC)^(1/Churn)))))




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Where:

        •   Acquisition cost = total average acquisition cost per customer
        •   Margin = the average monthly ongoing operator margin in dollar terms
            per customer excluding acquisition costs.
        •   WACC = monthly weighted average cost of capital
        •   Churn = total average monthly churn rate %
Note that the average customer lifetime is a function of the average churn rate.

Therefore, a 50% reduction in churn (for example) will approximately double the
lifetime net present value of an operator’s customer base.

Hence, whilst customer lifetime net present value is the key indicator used to
measure best practice, churn is also an important indicator.

2.2.5   Definitions Used in this study

The following table outlines the definitions used in this study for customer churn,
net adds, average revenue per user (ARPU), acquisition costs, net equipment
expense, operating margin, weighted average cost of capital (WACC) and
operational and capital expenses.




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CHURN:

Postpaid Monthly Churn:

Definition

Those customers disconnected in the month divided by average customers for the month.
Average customers equals beginning monthly subscribers plus the end of the month subscribers divided by two.

Prepaid Monthly Churn:

Definition

For prepaid customers, all disconnects of services in that month plus services that become inactive in that month divided by the average
customer base in that month. Please see the definition below for inactive customers.

Inactive customers - prepaid:

Definition

Defined as all customers (services) who have not made or received calls for at least three months.

Average monthly churn - prepaid and/or postpaid

Definition

Defined as a three month rolling average of monthly churn - prepaid or postpaid.

Average Voluntary churn - Postpaid

Definition

Those customers who themsleves choose to disconnect for any reason during a given month, divided by the average customer base
during that month (includes both contract and non-contract postpaid customers)

Average Involuntary churn - Postpaid

Definition:

Those postpaid customers who are disconnected in a given month at the initiative of the operator for bad debt or other operational
reasons, including fraud, divided by the average customer base during the month.

Rotational churn - Postpaid

Definition

A subset of voluntary churn. The percentage of voluntary churners who choose to disconnect and reconnect as a new subscriber to
the same operator in a given month. (Note: You may only know this % through market research for example)

Off contract churn - postpaid

Definition

Total annual churn for postpaid customers who are not on a contract for a given period, e.g. for the month or year.




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On contract churn - postpaid

Definition

Total annual churn for postpaid customers who are on their first contract for a given period, e.g. for the month or year.

Recontracted customer churn - postpaid

Definition

Total annual churn for postpaid customers for a given period (e.g for a month or a year) who have resigned a new contract after the
first contract has expired, e.g. under a recontracting promotional initiative.

Net additions

Definition

Gross additions less all disconnections in any given period.


Average Revenue Per User:

Definition

Please refer to the ARPU table in the Mobile KPI's and Benchmarks worksheet.

Average Acquisition Cost per customer:

Definition

Defined as total advertising and promotional costs (excluding brand advertising) plus third party commissions plus net equipment expense
per gross add.

Net equipment expense:

Calculated as follows:

Equipment-related activity
Equipment net expense (excluded)
                                                    (Equipment sales)
                                                    Equipment subsidies
                                                    Cost of equipment sales
                                                    Installation revenue
                                                    (Installation expense)
                                                    Direct payroll
                                                    Service center
                                                    Warehousing & distribution
                                                    Other


Gross monthly operating margin:

Definition

Defined as ARPU less operating expenses (marketing, customer service, network operations, billing, finance & administration), less
acquisition costs


Weighted Average Cost of Capital (WACC)

Definition:

The expected rate of return on capital invested.




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Operational Expenses (OPEX)

Definition:

Total operational expenditure on running everyday marketing campaigns (e.g. agency costs or handset subsidies)

Capital Expenses (CAPEX)

Definition:

The total investment in capital items in a given period (e.g. network, software licenses)



2.3 Participant Selection and Recruitment
Study participants were selected for their apparent expertise and recent success
record in at least one aspect of mobile customer retention, as observed by
Emagine’s customer retention consultants. Three regions were targeted and
subsequent operators were selected from Europe, Asia Pacific and the United
States who agreed to participate in Emagine’s diagnostic.

This study was limited to mobile operators or the mobile divisions of integrated
telecommunications operators to maximise the relevance of the findings to
participants.

2.4 Questionnaire Development
The questionnaire was designed to gather both qualitative and quantitative
data.

The questionnaire was developed following the publication of last year’s
diagnostic. A series of workshops were held with last years participants and
additional scope was identified. These workshops identified the key retention
and loyalty questions operators asked as well as potential gaps of information.
Where possible, participating operators were again given the opportunity to
contribute to questionnaire design. The questionnaire split the data between
Prepaid and Postpaid.

              •   The final questionnaire design comprised two components:
              •   A face-to-face or phone interview qualitative questionnaire, and
              •   Quantitative data workbooks, which were completed by the operator
                  prior to the qualitative interview (where possible)

2.5 Data Collection
The data-collection phase of the study was undertaken between May and July
2002.

This phase involved face-to-face and/or phone interviews spread across Europe,
USA and the Asia-Pacific. Each interview lasted approximately 1-2 hours and
often with 2 – 3 key people in each operator.



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Key people interviewed include where possible: CEO, Marketing Director,
Retention/CRM Director, Customer Service Director, Retention Manager, and
Senior Financial and Marketing Analysts.

In addition, participants were provided with the quantitative workbooks and
qualitative questionnaire prior to the scheduled interview.

2.6 Data Analysis
The initial phase of the analysis combined all the participating operator
information to formulate a single view of the data. This enabled key findings to
be identified. Emagine interpreted these findings to identify best practice
customer retention activities.

In a limited number of circumstances, where confidence in the data provided
was low and contributed to a significant skewing of the data, specific operator
data has been excluded from certain analysis.

In all cases, Emagine has based this report upon data provided directly from the
participants. Every effort has been made to ensure information portrayed in this
report is accurate and realistic. Where discrepancies occur Emagine holds no
liability for the accuracy of the specific information in question. The quality of the
final analysis and recommendations is based on Emagine’s expertise in the area
and the information supplied by the participants.

2.7 Case Studies
Case studies are used to provide a practical illustration of a particular Emagine
point of view or an example of a specific initiative.

Operator names are used in Case Studies that appear in this report, however
these operators are not necessarily participants in this study. Publicly available
information has been used for the case studies.




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3         Churn Management Strategies

    3.1   Overview
    Churn is one of the biggest problems facing both pre & post paid operators
    irrespective of the level of competition in the market.
    This report provides an overview of the effective churn management strategies
    that are being implemented by mobile carriers globally across both Prepaid and
    Postpaid customer bases.
    Specifically the report provides an assessment of the impact versus
    cost/complexity of the full range churn management strategies employed by
    operators, and best practice benchmarks achieved by operators.
    Finally the report looks at what types of offers are actually working to reduce
    churn.

    3.2   Executive Highlights
           •   As markets become increasingly competitive, Postpaid churn is
               contained for a while. There is a similar trend for Prepaid although not
               to the same degree.
           •   Operators ranked comprehensive customer information, reactive save
               and churn prediction as the top three important retention strategies
           •   25% of operators offer a real time value based, fully automated
               customer save process with extensive offers
           •   Best practice save rates for Prepaid are 19%, and Postpaid 65% of
               those customers contacted
           •   83% of medium to high MCI operators have a churn prediction solution
           •   Majority of operators have a campaign test team for Prepaid and
               Postpaid marketing strategies
           •   Over 93% of operators make customer value segmentation data
               available to marketing, customer service and customer save
           •   Over 80% of operators use customer value information in differentiating
               customer service and offers made to high value customers for
               Postpaid
           •   56% of operators are using churn prediction scores as a basis for
               making marketing offers to Postpaid customers
           •   37% of operators have achieved or exceeded their objectives for
               Prepaid recharge campaigns, whilst a further 25% are achieving
               partial objectives




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3.3 Introduction

3.3.1                             As markets become increasingly competitive operators get
                                  Postpaid churn under control… for a while


                         90.00%

                                        "Low"                                                         "Medium"                                           "High"
                         80.00%
                                                                            G


                         70.00%
                                                                                                                                                              AD

                         60.00%
                                                      A   C
 Annual Postpaid Churn




                                                                                                                                              AB

                         50.00%                                 E


                         40.00%                                     F                                                      Y
                                                                                                                                         AA
                                                                                 I
                                                                                              N             R      S       T
                         30.00%
                                       B
                                                                                  K
                                                                                          O                                                        AC
                         20.00%                                                                                        U W           Z
                                                                    H                M                      Q
                                                                                                                       V
                                                                                                                                          X
                         10.00%                       D
                                                                        J             L           P

                         0.00%
                              20%     25%       30%       35%   40%                  45%              50%        55%           60%        65%           70%        75%   80%
                                                                                Market Competitiveness Index (%)




Figure 3.1  Postpaid annual churn and Postpaid customer lifetime NPV by
   market competitiveness


                              •     Countries identified as “Low MCI”, are relatively cosy markets with low
                                    levels of competition. The focus is on growing market share quickly,
                                    and the consequent acquisition focus and aggressive marketing
                                    campaigns leads to high churn rates (on average 3.81%). In particular,
                                    high involuntary churn is experienced as customers are “sold” the
                                    benefits of a product they are unable to afford (bad debt) or from
                                    opportunists who take advantage of rudimentary credit screening and
                                    checking processes (leading to high rates of fraud).
                              •     As the level of competition in a market increases (moving from low to
                                    medium), there is a shift from a market share focus to a retention
                                    focus. Consequently, CRM systems and strategies are put in place and
                                    churn is substantially reduced. The average Postpaid churn rate for the
                                    Medium MCI stage is 1.73%. However, NPV also declines at this stage




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                                     due to aggressive price competition and marketing towards high
                                     value customers.
          •                          As the level of market competition reaches higher levels, churn
                                     increases again (to an average of 3.35%). In part this is a natural result
                                     of the higher level of competition in the market. However, this is also
                                     driven by a conscious decision by operators to allow certain low value
                                     customers to churn, while trying to retain higher valued customers
                                     through programmes and incentives. NPV tends to decline due to
                                     aggressive price cuts. To address this the company needs to focus on
                                     usage stimulation at this point.



3.3.2                              The degree of market competitiveness also impacts on the level of
                                   Prepaid churn in the same way, although not to the same degree


                                   120.00%

                                                "Low"                                                              "Medium"                                              "High"

                                                                                       G
                                   100.00%
                                                                                                                                       S




                                   80.00%
        Annual Prepaid churn (%)




                                                     A
                                                                         C


                                   60.00%                                                      H
                                                                                                               K
                                                                                                       M                                             V                         AD
                                                                                 I                                  P              R
                                                                                                                                                U
                                   40.00%        B                                                                                                       Z
                                                                                                           N                               W
                                                                             D
                                                                                                                                                              AA
                                                                                                   L
                                                                                                                          Q
                                   20.00%                                                                                      T
                                                                                                                                                                    AC
                                                                                                                   O
                                                                                           J                                               X
                                                               F                                                                                             AB
                                    0.00%
                                         20%   25%       30%       35%           40%               45%              50%       55%              60%            65%        70%        75%   80%
                                                                                               Market Competitiveness Index




Figure 3.2  Prepaid annual churn and Prepaid customer lifetime NPV by
   market competitiveness

          •                          Operators in low market competitiveness experience large swings
                                     between high and low churn and profitability. Indicative of the high
                                     average monthly Prepaid churn rate at this stage of 4.76%.
          •                          As market competitiveness increases operators begin to contain churn
                                     (average falls to 3.32%), however some still have churn levels of up to




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          50% and the average monthly Prepaid churn rate in comparison to
          Postpaid at the Medium MCI stage is still 91% higher!
      •   In the Medium MCI group, 5 out of 17 operators (nearly 30%)
          experienced a negative NPV for Prepaid customers. This is indicative of
          the pressure of competition in their market – they are churning Prepaid
          customers faster than they can profitably sustain them.
      •   Operators with negative NPV need to re-evaluate their commitment to
          the Prepaid market. If they want to remain a Prepaid player, their
          business model will need to be addressed and this will probably involve
          an injection of capital. Should they wish to exit the market, they can
          either sell off their Prepaid base to the highest bidder, with an
          immediate improvement in total NPV or they can investigate
          introducing a “credit challenged” Postpaid plan and transferring the
          Prepaid base across.
  •   Operators in highly competitive markets experience a small rise in churn
      although this is not as evident as in Postpaid. This is due to the levels of
      competition for Prepaid customers not being as high as for Postpaid
      customers as Prepaid customers are not perceived to be such high value.
      Best practice operators are experiencing strong Prepaid NPV results as
      they move into highly competitive markets, suggesting perhaps that they
      have managed to control Prepaid churn while maximizing Prepaid ARPU.




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3.4 Detailed Findings

3.4.1 Churn management strategy rankings
           •       Operators ranked churn                     management                     strategies               in    order          of
                   importance as follows:



3.4.1.1 Operators ranked comprehensive customer information, reactive
        save and churn prediction as the top three important retention
        strategies

   Comprehensive customer info                                                                                                    91%

                    Reactive save                                                                                             90%

                 Churn Prediction                                                                                           88%

            Proactive campaigns                                                                                       81%

                Tariff optimisation                                                                                80%

               Customer contracts                                                                                 79%

    Manage interactions/segment                                                                                   79%

 Handset resubsidisation/upgrade                                                                                78%

       Operational segmentation                                                                             75%

                 Recontract offers                                                                        73%

                  Loyalty program                                                                     70%

  Recharge campaigns (prepaid)                                                                      68%

   Migration strategies (post/pre)                                                            64%

                  Affinity program                                               54%

                SIM lock (prepaid)                                         48%

                                      0%   10%   20%   30%      40%       50%          60%          70%         80%         90%         100%
                                                                Average Importance Rating



Figure 3.3  Operators ranking of churn management strategies in order of
   importance

           •       The top 4 retention offers are Airtime offers (e.g. free minutes), Handset
                   upgrades, Contracts/Recontracting, and Rate Plan Optimisation.


3.4.2 Emagine Priority Matrix of Churn Management Strategies
Following is a priority matrix of Churn Management Strategies, as rated by the
participants in the study. Participants were asked to rate on a scale of 1 to 5 the
importance of each of these strategies in reducing churn in their organisations,
and the cost annually to their operation to implement these strategies.
The matrix is a priority roadmap of churn management initiatives used by
operators to proactively combat churn.



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To obtain a specific comparison between best practice and actual practice,
Emagine conducts a tailored “Emagine benchmark diagnostic”. This diagnostic
compares individual operators to the roadmap, and best practice benchmarks,
and the results of this are provided a tailored Emagine Diagnostic and
Recommendations report.
The range of possible strategies, and the importance of each indicate that there
are no silver bullets, and a range of quick wins’ versus higher cost high impact
initiatives required to effectively combat churn.

3.4.3                            Churn management strategies Impact versus cost complexity
                          100%



                                        QUICK WINS                                                                              HIGH COST/IMPACT
                                                                                             Comprehensive customer info
                                                                                        Reactive save
                                                                                 Churn Prediction


                                                                                                      Proactive campaigns
                          80%                                                                Tariff optimisation
                                         Manage interactions/segment
                                                                           Customer contracts
 Average Importance (%)




                                                                                                                                     Handset resubsidisation/upgrade
                                                       Operational segmentation
                                                                    Recontract offers
                                                                                                Loyalty program

                                                                   Recharge campaigns (prepaid)

                                                                   Migration strategies (post/pre)
                          60%


                                        LOW IMPACT                               Affinity program                                  NO RETURN



                                                               SIM lock (prepaid)




                          40%
                             0.00     < US$1M               1.00       US$1 - $5M                    2.00         US$5 - $20M          3.00     US$20 - $50M           4.00
                                                                                          Cost Complexity (US$)



Figure 3.4                               Impact versus cost complexity – churn management strategies

                                 •   The area to focus on initially is the Quick Win’s quadrant, followed by
                                     the High Cost/Impact quadrant.
                                 •   This chapter looks at each of these churn management strategies
                                     individually, and investigates the benchmarks and best practice within
                                     each area.
                                 •




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3.5 Churn Management Strategies - Best Practice Benchmarks

   Sum m ary of Best Pract ice Churn
         Managem ent St rat egies                                        Post paid                                              Prepaid
Co m p r eh en sive cu st o m er                   Nam e an d Ad d r ess f o r all cu st o m er s        Nam e an d Ad d r ess f o r 80% o f b ase
                                                   Em ail ad d r ess f o r o ver 80% o f b ase           Em ail ad d r ess f o r o ver 80% o f b ase
React ive Cu st o m er Save Pr o cess              Real t im e valu e b ased save f u n ct io n          Man u al cu st o m er valu e, r an g e o f o f f er s
                                                   65% save r at e                                       19% save r at e
Ch u r n Pr ed ict io n                            Up d at e ch u r n sco r es d aily                    Up d at e ch u r n sco r es m o n t h ly
                                                   70% o f ch u r n er s in t o p 2% sco r ed            N/ A
Pr o act ive Cam p aig n s                         Act ive t est m ar ket in g t eam                     Act ive t est m ar ket in g t eam
                                                   Pr ed ict ive ch u r n an d valu e b ased             Pr ed ict ive ch u r n an d valu e b ased
                                                   cam p aig n s                                         cam p aig n s
                                                   20-30 cam p aig n s p er m o n t h                    1-10 cam p aig n s p er m o n t h
Tar if f Plan Op t im isat io n                    Im p lem en t ed t ar if f p lan o p t im isat io n   Im p lem en t ed t ar if f p lan o p t im isat io n
Man ag e Cu st o m er In t er act io n b y         Dif f er en t iat e ser vice an d o f f er s b ased   Dif f er en t iat e ser vice an d o f f er s b ased
Seg m en t                                         o n cu st o m er valu e                               o n cu st o m er valu e
Cu st o m er Co n t r act s (Po st p aid ) / SIM   Use cu st o m er co n t r act s - act ive r e-
Lo ck (Pr ep aid )                                 co n t r act in g cam p aig n s                       Use SIM lo cks o n Pr ep aid h an d set s
                                                   Re-su b sid ise/ u p g r ad e cu st o m er
                                                   h an d set s at en d o f co n t r act - su b sid y    Re-su b sid ise/ u p g r ad e cu st o m er
Han d set Re-Su b sid isat io n / Up g r ad es     level sam e as acq u isit io n                        h an d set s af t er 18 m o n t h s
                                                   Cu st o m er seg m en t at io n in f o r m at io n    Cu st o m er seg m en t at io n in f o r m at io n
Op er at io n al Cu st o m er Seg m en t at io n   availab le in co r e d ivisio n s                     availab le in co r e d ivisio n s
Reco n t r act in g o f f er s (Po st p aid ) -    Act ive r eco n t r act in g cam p aig n s -          Act ive r ech ar g e cam p aig n s - o f f er s
Rech ar g e Cam p aig n s (Pr ep aid )             o f f er s b ased o n cu st o m er valu e             b ased o n cu st o m er valu e
                                                   Of f er lo yalt y p r o g r am f o r h ig h valu e    Of f er lo yalt y p r o g r am f o r h ig h valu e
Lo yalt y Pr o g r am s                            cu st o m er s                                        cu st o m er s
                                                   Act ive m ig r at io n o f cr ed it ch allen g ed
Mig r at io n St r at eg ies (Pr e/ Po st )        Po st p aid cu st o m er s                            React ive o n ly



Figure 3.5                Summary of best practice churn management strategies




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3.6 High impact churn management strategies

3.6.1 Obtain Comprehensive Customer Information


3.6.1.1 Operators have far more knowledge of their Postpaid base than
        their Prepaid base




                                Address details (eg postcode/city)0%6%                                             94%

                                  Usage at CDR level - outbound       7%0%7%                                           86%

                                    Usage at CDR level - inbound           15%    0%                                   85%

          Usage of services (voice mail, roaming, data, voice etc.)0%   13% 0%6%                                         81%

 Acquisition channels (eg. Web, TMR, dealers, franchises, CS etc)0%          25%                                             75%                                    0%
                                                                                                                                                                    < 30%
                        Personal details (eg. Name, age, gender)0%           25%                                             75%                                    30 - 50%
                                                                                                                                                                    50 - 80%
                       Contact details (home phone, work phone)0%           19%          13%         13%                             56%
                                                                                                                                                                    > 80%

                                Customer interaction - call centre          19%         6%     13%           19%                           44%

    Promotional tracking (eg. Whether customers accepted offers)            19%          13%         13%           19%                      38%

                                     Customer interaction - email                27%                       33%                      20%      0%        20%

               Profession (eg. income, occupation, work address)            19%                       44%                      6%     13%              19%

                    Customer preferences (eg. Interests, lifestyle)                      50%                                   31%                6%0% 13%

                                       Customer interaction - web                      40%                             33%                       20%     0%7%

                                           Contact details (email)    7%                                   73%                                    13% 0%7%

                               Customer interaction - dealer/shop                       44%                        19%               19%           13%       6%

                 Links between people (eg. Household, relations)                        44%                                  38%                       19%    0%

                                                                  0%        10%        20%    30%     40%        50%     60%       70%      80%        90%   100%




Figure 3.6  Percentage of operators who have certain information re their
   customer base - Postpaid




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                                   Usage at CDR level - outbound       8% 0%                                         92%

                                    Usage at CDR level - inbound           18%     0%                                     82%

          Usage of services (voice mail, roaming, data, voice etc.)     13%            13% 0%                                73%

 Acquisition channels (eg. Web, TMR, dealers, franchises, CS etc)     7%         14%         7%         14%                           57%

                                 Customer interaction - call centre                    43%                    0%7%   7%                       43%

    Promotional tracking (eg. Whether customers accepted offers)                 29%                      21%        7%    7%                     36%
                                                                                                                                                                           0%
                                      Customer interaction - email                     43%                                 36%                0%            21%
                                                                                                                                                                           < 30%
                    Customer preferences (eg. Interests, lifestyle)                                62%                                  23%            0%    15%           30 - 50%
                                                                                                                                                                           50 - 80%
                                Address details (eg postcode/city)0%                   40%                       20%                    27%                   13%          > 80%

                         Personal details (eg. Name, age, gender)0%                      47%                           20%                  20%               13%

                                       Customer interaction - web                            50%                                  36%                       7%0%7%

                               Customer interaction - dealer/shop                              57%                              14%         7%         14%        7%

                                            Contact details (email)                36%                                            64%                               0%

                       Contact details (home phone, work phone)         13%                               53%                           13%                 20%     0%

               Profession (eg. income, occupation, work address)                  33%                                  47%                          7%        13% 0%

                  Links between people (eg. Household, relations)                                       71%                                       21%             7%0%

                                                                  0%       10%         20%        30%     40%    50%       60%        70%        80%        90%     100%




Figure 3.7  Percentage of operators who have certain information re their
   customer base – Prepaid


              •        The collection of personal details (name and address) is very high
                       amongst Postpaid customers but substantially lower for Prepaid
                       customers. While 94% of operators have address details for over 80% of
                       their Postpaid base, whilst the corresponding figure is on 13% for
                       Prepaid.
Emagine point of view
The high proportion of Postpaid names and addresses is not surprising given the
requirement to send out the bill.
Operators who have address details for a substantial proportion of their Prepaid
base are likely to be operating in countries where it is a legal requirement to
collect basic customer information for all Prepaid customers.
In order to gather this information, often the first call made on a Prepaid phone is
routed to a customer service agent who collects the details over the phone.
While this does not prevent inaccurate information being given, it does provide
some assistance in understanding who the customer is.
Other operators have provided credits (sent out in the email) in return for
customer information, name and address.
              •        Email address has been difficult to obtain for both pre and Postpaid
                       customers. 80% of Postpaid operators and all Prepaid operators have
                       less than 30% of their respective base’s contact email address.


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      •   Prepaid operators have also found it difficult to collate alternative
          contact details (home or work phone number) with 66% of operators
          having this information for less than 30% of the base.
      •   The most difficult information to obtain for both pre and Postpaid
          customers is that regarding customer interaction with the company
          and more in-depth personal information such as preferences and
          family relationships.
Emagine point of view
The lack of customer interaction information is probably due to automated
processes not being properly put in place to capture this information and sort it
efficiently. To obtain greater personal information, incentives need to be
provided which directly relate to the information the company is wanting to
collate. For example developing a plan which takes into account the links
between people, or providing rewards for loyalty based on their lifestyle
preferences. This exact problem drove the introduction of Loyalty schemes in the
airline industry some 15 years ago for example.
      •   Information regarding phone usage – inbound, outbound and services
          - has been obtained for over 80% of the base for both Prepaid and
          Postpaid customers. This is due to it being easy for the operator to
          collect this information as it is all automated and they are not reliant
          on the customer provider or third parties providing information




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3.6.2 Implement Reactive Customer Save Process


3.6.3   All operators in the study offered at least a basic customer save function
        with some offers. 25% of operators offer a real time value based, fully
        automated customer save process with extensive offers



                               0%
                               0%                      No customer save function

                                                       Basic customer save function / No offers
                25%
                                                       Basic function (no value calculation) / Some offers

                                          31%          Manual customer value calculation / Extensive offers

                                                       Real time value based / Fully automated process / Extensive
                                                       offers




                         44%




Figure 3.8      Reactive save status of operators – Postpaid

        •    The majority of operators (44%) have customer save teams with a
             manual customer value calculation and extensive offers.
        •    The largest customer save team in this study is at 1200 representatives
             conducting both proactive and reactive customer saves.
Emagine point of view
As predicted lest year, the importance of a customer save team has only
increased as markets become more competitive and cellular penetration
continues to increase.
An effective customer save team should be one of the first customer retention
strategies adopted by any operator serious about reducing customer churn
(refer to Impact and Cost/Complexity Matrix).
Many operators interviewed in this study are in the process of moving their
customer save teams to a more automated process with more detailed
customer value segmentation and predictive technologies for churn propensity
and best offer selection for individual customers.



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3.6.4    Though only 50% of operators in the study have a customer save function
         for Prepaid customers, 44% offer at least a basic function with some save
         offers.


                                      0%
                         13%




                                                                               No customer save function

                                                                               Basic customer save function / No offers

                                                          50%                  Basic function (no value calculation) / Some offers


          31%                                                                  Manual customer value calculation / Extensive offers

                                                                               Real time value based / Fully automated process / Extensive
                                                                               offers




                               6%




Figure 3.9         Reactive save status of operators – Prepaid

         •      Though in its early stages for many operators, customer save functions
                are on the increase for Prepaid customers. Majority of Prepaid save
                functions are proactive based on a Prepaid customers drop in usage
                or extension of times between recharges.

3.6.5    Best practice save rates for Prepaid are 19%, and Postpaid 65% of those
         customers contacted.


CUSTOMER SAVE PERFORMANCE:                              Best Practice KPI's:              Averages:
                                                       Postpaid:    Prepaid:        Postpaid:   Prepaid:
Percentage of potential churners targeted                100%        100%                66%                      43%
Percentage of churned customers contacted                92%          50%                52%                      26%
Retention rate (of those contacted)                      65%          19%                41%                       7%
Retention rate (those with operator 6 months later)      100%          #                 58%                         #
Average call handling time per save (minutes/save)        2.4          #                  8.93                       #
Average cost per save (US$PPP)                           $5.37       $5.48             $56.84                    $5.48

Figure 3.10        Best practice and Average customer save performance indicators




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3.6.6   81% of operators only consider high value Postpaid customers for
        targeting by customer save teams while 19% consider all Postpaid
        customers.
 100%                0%


  90%               19%
                                               27%

  80%


  70%


  60%

                                               40%              No customers considered for save
  50%                                                           All customers, regardless of value
                                                                Only certain high value customers


  40%               81%



  30%


  20%
                                               33%

  10%


  0%
                  Postpaid:                   Prepaid:



Figure 3.11 Percentage breakdown of what customers operators consider for
   save - Postpaid versus Prepaid

        •   Prepaid save functions for 40% of operators consider all Prepaid
            customers while 33% of operators only consider high value Prepaid
            customers for their customer save teams. Admittedly many operators
            are yet to conduct extensive customer value segmentation of their
            customer base, which is why all Prepaid customers are targeted for
            these operators.




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3.6.7   50% of churning customers are contacted for Postpaid while on average
        only 17% of Prepaid churning customers are contacted by customer save
        teams




 80%
                                                       Percentage of potential churners targeted
                                                       Percentage of churned customers contacted

 70%
                 66%


 60%

                                   52%
 50%
                                                 43%

 40%



 30%
                                                                     26%


 20%



 10%



  0%
                       Postpaid:                       Prepaid:



Figure 3.12 Comparison of average percentage of potential churners targeted
   against average percentage of churned customers contacted – Postpaid
   versus Prepaid

        •   Bets practice for contacting churning customers is for a 92% contact
            rate by an operator running a customer save team of about 100 full
            time representatives. Some customers are contacted by direct mail
            and SMS to enable the widest possible coverage by the team.




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3.6.8   On average 41% of contacted Postpaid customers are saved by customer
        save teams of which 58% are still with the operator six months later



 80%
                                                     Retention rate (of those contacted)
                                                     Retention rate (those with operator 6 months later)

 70%



 60%                             58%



 50%


               41%
 40%



 30%



 20%



 10%                                           7%


                                                                     0%
  0%
                     Postpaid:                      Prepaid:



Figure 3.13 Comparison of average retention rate of those contacted against
   average retention rate of those with operator 6 months later – Postpaid versus
   Prepaid

(Note: No data was provided for Prepaid retention rate after 6 months)
        •   Though the above chart is an average for all operators Postpaid
            customer save teams, best practice allows for a consistent 65% save
            rate with 100% retention rate with the operators six month later.




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3.6.9         Most highly effective save offers for Postpaid customers are handset
              upgrades, contracts/recontracting offers and air time offers



                              Handset upgrade            19%    0%6%                  25%                            50%                       Not applicable
                                                                                                                                               Not effective
                                                                                                                                               Average
                      Contracts/Recontracting                  33%               0%    13%                33%                    20%
                                                                                                                                               Effective
                                                                                                                                               Highly effective
              Air time offers (eg free minutes)      13% 0%            25%                              44%                      19%


                        Rate plan optimisation           20%     0%        13%                          53%                         13%


                     Bill and / or call discounts   6%   6%                31%                                44%                   13%


         Migration offers - postpaid to prepaid                            53%                     0%   13%                27%         7%


                Accessories (eg extra battery)                       44%                                  38%                    19%      0%

   New value-added services (e.g.mobile data
                    etc)
                                                                 40%                         13%                    40%                7%0%

 Value added services for both network & non-
                   network
                                                     13%         13%                                60%                             13%   0%


         Migration offers - prepaid to postpaid                                              93%                                       7% 0%


                                       SIM lock                                        80%                                   7%0%   13%   0%

       Third party offers (eg holidays, gift with
                      purchase)
                                                                           56%                                      31%             13% 0%




Figure 3.14 Percentage breakdown of customer save offer effectiveness –
   Postpaid

              •        The top three most effective offers include, rate plan optimisation,
                       airtime offers and bill and/or call discounts. The most ineffective offers
                       include accessories and third party offers.
              •        Clearly offers closely related to a customer’s service are more
                       effective in saving customers, such as handsets, airtime discounts and
                       rate plan optimisation. Interestingly only 7% of operators rated new
                       value added services (data etc.) as effective save offers while 40%
                       said they were average.
Emagine point of view
Customers remain relatively simple creatures – being on the right price plan, and
receiving good value for money remain the very basic needs of the customer.
If operators are to increase the take-up of value added services as rewards to
customers they will have to start making the offers more attractive. All operators
agree that to increase data products take-up they will have to have customers
trailing new services and as a cost effective save offer they are potentially
under-utilised.
Conversely, operators must be sensitive not to “push” solutions to customers that
don’t resolve the problem, simply to attempt to stimulate take-up of unwanted




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data services. SMS took 10 years to develop, and operators may need some
patience to wait for the market to catch up to the technology.
Free trials of value added data services have proven to be a successful means
to stimulating take-up .



3.6.10 Handset upgrades followed by SIM lock and air time offers are proving the
       most effect customer save offers for Prepaid customer save


                                                                                                                                   Not applicable
                                                                                                                                   Not effective
         Migration offers - postpaid to prepaid                                100%                                           0%   Average
                                                                                                                                   Effective
                                                                                                                                   Highly effective
                      Contracts/Recontracting                                91%                                     0% 9% 0%


                Accessories (eg extra battery)                               91%                                     0% 9% 0%


                     Bill and / or call discounts                      82%                                 0% 9%         9% 0%


                        Rate plan optimisation                         80%                                0%     20%          0%

   New value-added services (e.g.mobile data
                    etc)
                                                           60%                           0%         30%                10% 0%

       Third party offers (eg holidays, gift with
                      purchase)
                                                                 70%                                10%          20%          0%


                              Handset upgrade               64%                               0%     27%                 9%


         Migration offers - prepaid to postpaid             64%                               0%   18%             18%        0%

 Value added services for both network & non-
                   network
                                                            64%                               0%     27%                 9% 0%


              Air time offers (eg free minutes)           55%                      0%     18%                  27%            0%


                                       SIM lock     36%                 9%         18%                    36%                 0%




Figure 3.15                     Percentage breakdown of customer save offer effectiveness –
   Prepaid

              •        As with Postpaid customers, Prepaid customer save offers most
                       effective in reducing Prepaid customer churn are closely related to
                       the customers service, such as handsets and airtime offers.
              •        SIM lock on average to effective scores rates highest as save tool
                       (54%), though being somewhat a preventative measure adopted with
                       new connections rather then a proactive save offer.
              •        Many countries are also facing difficulty where people are unlocking
                       Prepaid SIM locks and selling handsets on the ‘black market’. This
                       problem opens the operator up to all kinds of problems when they
                       subsidise or re-subsidise handsets and are unable to realise a return on
                       their customers undertaking these activities.




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3.6.10.1 Case Study: Prepaid handset upgrade program launched with
   great success
  Prepaid handset upgrade program launched with great success
  Introduction:


  The following case study from an operator in the Irish mobile market,
  Vodafone Ireland, is strong evidence to support the business case viability of
  implementing a Prepaid handset upgrade program to achieve cost savings
  and reduce Prepaid churn.
  Issue:


  The Irish mobile market has an overall strong Prepaid customer base. 70% of
  Vodafone Ireland’s customer base is Prepaid. This market is quite established
  with a mobile penetration rate of 78%.             An increase in market
  competitiveness particularly since the entrance of a new competitor in 2001
  has seen operators move away from lowest cost Prepaid packages to
  targeting higher value customers and focusing strongly on improving
  retention. MNP will be introduced in September 2002.
  After conducting some research into why their Prepaid customers were
  leaving, Vodafone Ireland discovered that 60% of their customers were not
  churning at all but coming back to them. They realised a high proportion of
  their base was connecting, loading their free credit to their handset and then
  later reconnecting as a new subscriber to get a new handset and the free
  credit. Vodafone Ireland found they had provided no ability for their Prepaid
  customers to formally upgrade their handset while remaining a Prepaid
  customer.
  Options explored:


  The implementation of a handset upgrade program was the option chosen
  due to its convincing business case based on the strong cost savings resulting
  from upgrading customers versus treating them as a new customer.
  Solution implemented:


  A new ‘Prepaid Upgrade Pack’ was introduced, consisting of a new handset
  and more free credits than they would be entitled to as a new acquisition.
  Hence, they could get a new handset, more free credit and not have to
  change their mobile phone number. Plus, if the customer registered their new
  personal details they received 20 euro bonus credit. A benefit they would
  not have received if they simply registered as a new customer.




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   Results:


   Vodafone Ireland’s Prepaid handset upgrade program has been a success.
   Prepaid acquisition costs have fallen with the reduction in Prepaid handset
   subsidies and commissions payed for connecting new customers. Rotational
   churn reduced by 50% and their overall Prepaid churn rate was cut by 7-8%.
   * Note: Operator case studies are not necessarily participants from this study



3.6.11 Use Churn Prediction in Operations


3.6.12 83% of medium to high MCI operators have a churn prediction solution



    90%                                                                            yes
                                                        83%                        no


    80%
                                   75%


    70%


    60%


    50%


    40%


    30%
                   25%


    20%                                                                      17%


    10%


     0%
                         Low MCI                              Med-High MCI



Figure 3.16 Percentage breakdown of whether operators have a churn
   prediction solution in place – split by market competitiveness

      •   There is a marked increase in operators who have a churn prediction
          solution from 25% of operators in low MCI to over 80% of operators in
          medium to highly competitive markets.




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3.6.13 68% of operators are churn propensity scoring Postpaid customers at least
       monthly


                                                        No campaigns / No predictive churn scoring
                         6%
                                                        Ad hoc proactive camaigns / Ad hoc churn scoring
                    6%
                                                        Ad hoc proactive campaigns / Use of churn prediction score,
                                         25%            updated Monthly
                                                        Proactive strategies only /Use of churn predictive score, updated
                                                        at least Daily
                                                        Proactive and Reactive strategies / Use churn prediction score,
                                                        updated at least Daily




                                               13%




              50%




Figure 3.17     Churn prediction status of operators - Postpaid

      •   A large number of operators who have churn prediction software
          (19%) only use the software on an ad hoc basis both for scoring and for
          executing marketing campaigns




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3.6.14 75% of operators are yet to use churn prediction campaigns for Prepaid
       customers


                             0%
                             0%                       No campaigns / No predictive churn scoring
                  13%
                                                      Ad hoc proactive camaigns / Ad hoc churn scoring

                                                      Ad hoc proactive campaigns / Use of churn prediction score,
                                                      updated Monthly
                                                      Proactive strategies only /Use of churn predictive score, updated
                                                      at least Daily
                                                      Proactive and Reactive strategies / Use churn prediction score,
                                                      updated at least Daily




      19%




                                           63%




Figure 3.18       Churn prediction status of operators - Prepaid

      •     Though a high proportion of operators are yet to use predictive churn
            technologies for Prepaid customer retention campaigns a significant
            number of operators, one in four, are using churn prediction for
            Prepaid retention to some success.
      •




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3.6.14.1 Case Study: European operator uses simple and effective
         Prepaid churn prediction model
  European operator uses simple and effective Prepaid churn prediction model
  Introduction:
  Churn propensity is a big focus for this European operator. Lifecycle
  campaigns are given less emphasis as they believe most consumers who
  connect with them have been on other networks and know how to use their
  phone etc. Up to 70% of their customer base is Prepaid and interestingly a
  number of these Prepaid customers are high value subscribers.
  This operator has built a Prepaid churn prediction model to help them
  maintain and stimulate usage, reduce churn and target campaigns
  effectively.
  Options explored:
  This operator had previously developed a churn prediction model for their
  Prepaid base based on segmenting customers based on tenure and spend
  and identifying any subscriber who moved outside their group. However,
  they found it was not individualised enough. A simple and straightforward
  churn prediction model was required which would capture the spontaneity
  of Prepaid consumer recharge behaviour.
  Solution implemented:
  A model, called the Traffic Light Model was developed where a tolerance
  limit in terms of the average period of time between recharges is set per
  customer. Twice a week the usage of each Prepaid customer is analysed
  and if the time of inactivity exceeds this tolerance limit the customer is
  allocated a colour based on churn risk. See below:
  Green – 1.96 standard deviation points from the tolerance limit. (For example,
  if this limit was 7 days they are coded Green if they have not recharged
  between 7-14 days).
  Amber – Between 1.96–2.57 standard deviation points from the tolerance limit
  (ex. Between an estimated 14 – 19 days since recharge)
  Red – Between 2.57 – 3.5 standard deviation points from tolerance limit (ex.
  Between an estimated 19-26 days since recharge)
  Super Red - > 3.5 standard deviation points from tolerance limit (ie. Greater
  than a month since recharge)




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   All Super Red customers were contacted directly to encourage recharge
   and prevent churn and if they called the company directly the CS
   representative would know their Super Red status and make them an offer.
   Results:
   This model has proven effective for this operator essentially as it is an
   individualised approach to Prepaid churn prediction which takes into
   account the spontaneity of Prepaid consumer recharge behaviour and
   provided sound churn score information to use for proactive and reactive
   campaigns. However, when directly calling Super Red customers to prevent
   churn it was found that those who answered had either just been on holiday
   etc and those customers who did not answer had already churned. Also, It
   was found that once a customer became Super Red only 26% of these
   customers spontaneously topped-up. Hence, it was clear the model had to
   be reviewed and incorporate an understanding of Prepaid churn reasons –
   and gather a profile of those customers who had been Green and then
   become Super Red.
   * Note: Operator case studies are not necessarily participants from this study
       •

3.6.15 Best practice churn prediction scoring scored 70% of churning customers
       in the top 2% of churned customers


                                                                       Operator X
 90%                                                                   Operator S
                                                                       Operator L
                                                                       Operator K
 80%                                                                   Operator F
                                                                       AVERAGE

 70%


 60%


 50%


 40%


 30%


 20%


 10%


  0%
                2%                       5%                10%
                              Percentage of Churners (%)




Figure 3.19      “Lift curve” achieved by some operators and the overall average
   - Postpaid


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     •   Five operators in this study provided detailed information on the
         success of their churn prediction models. On average 31% of churning
         customers were found in the top 2% of scored customers, 38% in the
         top 5% and 54% in the top 10% respectively.
     •   Two operators have achieved best practice in churn prediction with
         over 64% of churning customers being found in the top 2% of scored
         customers and over 79% in the top 10%. These results provide an
         operator with excellent resource allocation capabilities (headcount
         and offer) where they can execute churn reduction campaigns to 10%
         of their customer base and target over 79% of customers predicted to
         churn in the near future.
  Emagine point of view
  In markets of increasing competition and shrinking margin on voice services
  the utilisation of churn prediction technologies can provide for an optimum
  allocation of resources for operators to address customer churn. Offers for
  customers can be of higher value and staff resources are kept at a minimum.
  Despite the current ‘desire’ for all operators to purchase churn predictive
  technologies many operators are conducting their own churn prediction
  analysis to some success. End of contract is always a primary indicator and
  many operators execute excellent end of conduct re-subsidisation of
  handsets and recontracting offers to minimise the impact of customers
  coming off contract. As a first step this form of ‘predictive’ retention strategy
  can be executed simply by pulling a monthly list from your billing system and
  test marketing some campaigns and offers to find what works best for your
  market.




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3.6.16 Conduct Proactive Campaigns


3.6.16.1 Majority of operators have a campaign test team for Prepaid
         and Postpaid marketing strategies


 80%
                                                                       Yes
                72%                                                    No

 70%



 60%


                                                 50%             50%
 50%



 40%



 30%                             28%



 20%



 10%



 0%
                      Postpaid                         Prepaid



Figure 3.20    Percentage of operators who have a proactive campaign test
   team – Postpaid versus Prepaid


       •   A greater proportion of operators have campaign testing teams for
           Postpaid campaigns than for Prepaid (72% versus 50%). Market
           competitiveness appears to have no impact on whether an operator
           has a campaign test team.




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3.6.16.2 Postpaid operators are becoming more sophisticated in their use
        of marketing tools for campaign management but still lag behind
        for Prepaid campaigns



                              6%
                                   0%                     No proactive campaigns run

                                                          Basic ad hoc campaigns run, but no campaign m'gt system

                                                          Lifecycle campaigns only run (recontract/resubsidise), some test
                                                          marketing, no campaign m'gt system
         29%
                                                          Some test marketing, predictive churn and value based
                                                          campaigns run, use campaign m'gt system,
                                                    24%   Active test marketing team, predictive churn and value based
                                                          campaigns run, use campaign m'gt system




                        41%




Figure 3.21    Proactive campaign management status of operators - Postpaid




                12%


                                              24%




        12%

                                                                No proactive campaigns run

                                                                Basic ad hoc campaigns run, but no campaign m'gt system

                                                                Lifecycle campaigns only run (recontract/resubsidise), some test
                                                                marketing, no campaign m'gt system
                                                                Some test marketing, predictive churn and value based
                                                                campaigns run, use campaign m'gt system,
                                                                Active test marketing team, predictive churn and value based
                                                                campaigns run, use campaign m'gt system


        18%




                                        35%




Figure 3.22    Proactive campaign management status of operators - Prepaid


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        •   70% of Postpaid operators conduct at least some test marketing using
            predictive churn and value based management tools and 30% of
            Postpaid operators are actively test marketing.
        •   The use of churn management and value based systems in
            conducting campaigns for the Prepaid base is substantially lower. Only
            24% of operators are conducting some test marketing using churn
            management or value based CRM. This is a reflection of the infancy of
            sophisticated customer management systems for the Prepaid base.



3.6.16.3 Most operators test between 0-10 campaigns per month for both
         pre and Postpaid

 100%                                                    0%
                        7%

  90%                   7%


  80%


  70%

                                                                           > 40
  60%                                                                      30 - 40
                                                                           20 - 30
                                                                           10 - 20
  50%                                                   100%               0 - 10


                       87%
  40%


  30%


  20%


  10%


  0%
                     Postpaid:                         Prepaid:




Figure 3.23    Percentage breakdown of the average number of campaigns
   tested per month – Postpaid versus Prepaid


        •   This is most likely a reflection of operators choosing to concentrate
            their marketing expenditure on a few key initiatives rather than active
            promotion of every product.
        •   Operator Y is testing 10-20 campaigns per month and operator W is
            testing between 20-30 campaigns per month for Postpaid customers.




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3.6.16.4        The majority of campaigns tested are deployed

                                                           84%
   85%
                          80%
   80%

   75%

   70%

   65%

   60%

   55%

   50%

   45%

   40%

   35%

   30%

   25%

   20%

   15%

   10%

    5%

    0%
                        Postpaid                          Prepaid




Figure 3.24    Average percentage of campaigns actually deployed per month
   – Postpaid versus Prepaid

         •   Over 80% of campaigns tested are deployed on average. This
             suggests either that the marketing groups developing the campaign
             ideas understand their markets well, developing successful campaigns.
             Alternatively it can suggest that there is insufficient time (due to
             competitive pressures), resource or budget to devise alternate
             campaigns and consequently only really poorly performing
             campaigns are pulled before a full-scale launch.




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3.6.16.5 Most operators conduct their campaign management activities
        in-house



                                                                                                   100%
   Campaign tracking & analysis
                                                19%


                                                                                                   100%
                 List production
                                     6%



 Telemarketing/customer service                                                              94%
           (inbound)                                  25%
                                                                                                          In-house
                                                                                                          Outsourced

                                                                                       88%
      Campaign design/creation
                                                      25%



  Customer database/Marketing                                                          88%
     database management                  13%


                                                                          69%
      Telemarketing (outbound)
                                                                    63%


                                                              44%
             Fulfillment logistics
                                                                                 81%




Figure 3.25     Percentage breakdown of whether operators are conducting
   their proactive activities in-house versus outsourced – Postpaid




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                                                                                         88%
   Campaign tracking & analysis
                                       6%


                                                                                  81%
                   List production
                                            13%


                                                                            75%
      Campaign design/creation                                                          In-house
                                                  31%
                                                                                        Outsourced



  Customer database/Marketing                                               75%
     database management               6%



 Telemarketing/customer service                                             75%
           (inbound)                        13%


                                                                50%
      Telemarketing (outbound)
                                                          44%


                                                          44%
               Fulfillment logistics
                                                                50%




Figure 3.26     Percentage breakdown of whether operators are conducting
   their proactive activities in-house versus outsourced - Prepaid


           •        Fulfilment logistics and outbound telemarketing are the most likely
                    activities to be outsourced for Postpaid campaigns. This is probably a
                    reflection of the nature of these activities in that they are not generally
                    part of core business skills and also require a large amount of
                    infrastructure to undertake properly. Outsourcing companies can
                    generally provide these services more cheaply than if an operator
                    conducted them internally as fixed costs are amortized over many
                    businesses.
           •        Prepaid campaigns are far more likely to be conducted in house for all
                    activities with the exception of fulfilment. The same reasons as for
                    Postpaid apply here.




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3.6.17 Implement tariff plan optimisation




                              0%   6%



                                           13%




                                                           No plans for program
                                                           Strategy under development
                                                           Implemented / achieving partial objectives
                                                           Implemented / meeting core objectives
                                                           Implemented / objectives met beyond expectations



           56%


                                                 25%




Figure 3.27    Percentage breakdown of the use of tariff plan optimisation by
   operators and     their effectiveness

       •     56% of operators have implemented a tariff plan optimisation service
             for their customers, which has met their business objectives. A further
             25% have introduced the service, and it is partially meeting their
             objectives.




Emagine Point of View
The extent that rate plan optimisation is used internally versus externally was not
specifically covered this year in this study. However clearly it has rated very highly
as an operator specific strategy to reduce churn.
Several operators reported that they use the optimisation service and “right
plan” customers proactively every 3 months.
Other operators use rate plan optimisation as one indicator in churn propensity
modelling. One operator reported that their analysis showed that if a customers
is greater then >2 rate plans away from their “best plan”, then they have a
higher propensity to churn. Customers who are only 1 plan away from the “best
plan” do not show a significantly higher propensity to churn.


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The critical question is whether the decrease in ARPU due to “right planning” all
customers is actually justified by the decrease in churn (increase in lifetime
value). No operator was able to provide such results in the study.
Emagine has calculated a “rule of thumb” model below to determine the
necessary churn reduction required in order to justify the decrease in revenue
due to optimisation.


     Assumptions (inputs in Blue)                                                      Scenario 1          Scenario 2          Scenario 3
     Number of Customers                                                                   1,000,000           1,000,000           1,000,000
     Monthly Churn Rate                                                                           2.5%                2.5%                2.5%
     Average acquisition costs                                                     $               250 $              250 $                250
     Average Revenue per customer per month                                        $                60 $                60 $                60
     Gross Margin                                                                                  50%                50%                  50%
     Average Margin per month per customer                                         $                30 $                30 $                30
     Average Annual Churn rate                                                                     30%                30%                  30%
     Average decrease in revenue if all customers optimised                                     -2.5%               -5.0%               -7.5%

     Current Cost of Churn
     Number of lost customers per annum                                                      300,000             300,000             300,000
     Annual Lost Margin per annum (annualised)                                     $     108,000,000   $     108,000,000   $     108,000,000
     Wasted acquisition cost                                                       $      75,000,000   $      75,000,000   $      75,000,000
     Total Annual Cost of Churn currently                                          $     183,000,000   $     183,000,000   $     183,000,000

     Optimisation Cost
     Number of customers optimised                                                         1,000,000           1,000,000           1,000,000
     Total margin of base annualise - pre optimisation                             $     360,000,000 $       360,000,000 $       360,000,000
     Average decrease in revenue due to optimisation                                             -3%                 -5%                 -8%
     Total margin of base annualise - after optimisation                           $     351,000,000 $       342,000,000 $       333,000,000
     Total Annual Cost of optimisation                                             $       9,000,000 $        18,000,000 $        27,000,000

     Break even calculation
     Decrease in cost of churn required to break even                              $       9,000,000   $      18,000,000   $       27,000,000
     Decrease in cost of churn required to get 100% ROI                            $      18,000,000   $      36,000,000   $       54,000,000

      Number of lost customers per annum required                                  $         274,542   $         248,311   $         221,269
      Annual Lost Margin per annum (annualised)                                    $      96,364,393   $      84,922,297   $      73,682,676
      Wasted acquisition cost                                                      $      68,635,607   $      62,077,703   $      55,317,324
      Total annual cost of churn post optimisation required                        $     165,000,000   $     147,000,000   $     129,000,000
      Decrease in total cost of churn achieved                                     $      18,000,000   $      36,000,000   $      54,000,000

      New Annual Churn Rate required to reach 100% ROI following optimisation                    27%                 25%                 22%
      Old Annual Churn Rate                                                                      30%                 30%                 30%
      % decrease in churn rate required to reach 100% ROI following optimisation                  8%                 17%                 26%



Figure 3.28     Churn reduction required to justify decrease in ARPU due to rate
   plan optimisation (ROI 100% in 12 months)

   (Note: for a free copy of the above model, please email info@Emagine-
   int.com)
   The model above contains 3 scenarios for Carrier x, with 1M customers, and
   an annual churn rate of 30% pa.
       •      In scenario 1, the carrier has calculated that by optimising all
              customers they will immediately reduce the ARPU of the customer
              base by and average of 2.5%.
       •      In this case the cost to the carrier over the subsequent 12 months will
              be $9M. To justify the cost it has been assumed that the carrier would
              need to see a return of 100% (ie $18M) within 12 months due to churn
              reduction.



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     •   Therefore the required result has been calculated in terms of churn
         rates, and the % reduction in churn, which gives a saving of $18M
         within 12 months.
     •   In scenario 1, the carrier must be confident that optimisation will
         reduce churn rates from 30% p.a. to 27% p.a. (an 8% decrease) in
         order to justify the lost ARPU.
     •   In scenario 2, the carrier has calculated that by optimising all
         customers they will immediately reduce the ARPU of the customer
         base by and average of 5%. IN this case the cost to the operator is
         $18M, and required return A$36M.
     •   In scenario 2, the carrier must be confident that optimisation will
         reduce churn rates from 30% p.a. to 25% p.a. (a 17% decrease) in
         order to justify the lost ARPU.
     •   In scenario 3, the carrier has calculated that by optimising all
         customers they will immediately reduce the ARPU of the customer
         base by and average of 7.5%. In this case the cost to the operator is
         $27M, and required return A$54M.
     •   In scenario 3, the carrier must be confident that optimisation will
         reduce churn rates from 30% p.a. to 22% p.a. (a 26% decrease) in
         order to justify the lost ARPU.




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3.6.18 Manager Customer Interaction by Segment


3.6.19 Over 80% of operators use customer value information in differentiating
       customer service and offers made to high value customers for Postpaid




 Call routing based on value to higher                                       81%
               skilled reps                    13%



                                                                             81%
         Call routing to front of queue
                                                     19%



                                                                             81%
         Offers made based on value
                                                            31%



   Differentiated service levels based                              63%
       on value - more time spent                    19%                      Postpaid:
                                                                              Prepaid:


     Do not use value segmentation             13%
   information in any interactions with
               customers:                                           63%



     Longer opening hours based on        0%
                 value                    0%




Figure 3.29    How operators are using customer value segmentation
   information in their customer interactions – Postpaid versus Prepaid

            •      A high percentage of operators (63%) are yet to use customer value
                   information to differentiate customer interactions to Prepaid
                   customers. Some operators are in the process of differentiating
                   customer interactions for Prepaid customers with offers made to
                   customers and service level in the call centre.




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3.6.20 For Prepaid, no operators in low MCI markets in the study are actually
       using customer value information in customer interactions




      Do not use value segmentation                                  50%
    information in any interactions with
                customers:                                                               100%



                                                               42%
          Offers made based on value
                                           0%


                                                                                   Med-High MCI
                                                      25%                          Low MCI
          Call routing to front of queue
                                           0%



 Differentiated service levels based on               25%
        value - more time spent            0%



  Call routing based on value to higher         17%
                skilled reps               0%



                                           0%
 Longer opening hours based on value
                                           0%




Figure 3.30   How operators are using customer value segmentation
   information in their customer interactions – Prepaid split by market
   competitiveness

Emagine point of view
The priority for operators segmenting Prepaid customers on value is obviously
increasing with the majority of operator’s gross additions now coming from this
segment.
Operators are starting to recognise that high value customers can come from
their Prepaid base and warrant preferable treatment rather then just targets for
customer migration strategies to Postpaid.




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3.6.21 56% of operators are using churn prediction scores as a basis for making
       marketing offers to Postpaid customers




                                                                        56%
  Offers made based on churn score
                                              13%




      Do not use churn prediction                                 44%
  information in any interactions with
              customers:                                                                88%




  Differentiated service levels based               19%
  on churn score - more time spent       0%

                                                                                      Postpaid:
                                                                                      Prepaid:

 Call routing to front of queue based         13%
            on churn score               0%




 Call routing based on churn score to         13%
           higher skilled reps           0%




Figure 3.31   How operators are using churn prediction information in their
   customer interactions – Postpaid versus Prepaid

           •      While not insignificant, few operators are using churn prediction
                  scoring to determine the most effective marketing offers to be made
                  to Prepaid customers (13%).
           •      Though churn prediction for Prepaid customers is in its early stages for
                  many operators, all agree that there effort in this area will only
                  increase now they have some success with Postpaid customer churn
                  prediction campaigns.




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   3.6.22 The more competitive the market, the more likely that churn prediction
          scoring on Postpaid customers is used




                                                                           67%
  Offers made based on churn score
                                                    25%




      Do not use churn prediction                            33%
  information in any interactions with
              customers:                                                               75%




Differentiated service levels based on        17%
    churn score - more time spent                   25%


                                                                        Med-High MCI
                                                                        Low MCI
  Call routing to front of queue based   8%
             on churn score                         25%




 Call routing based on churn score to    8%
           higher skilled reps                      25%




   Figure 3.32   How operators are using churn prediction information in their
      customer interactions – Postpaid and split by market competitiveness




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3.6.23 69% of operators send more frequent and expensive marketing
       communications to high value customers



      Offer differentiated based on                                                                   81%
             customer value                                         38%



  More frequent communications to                                                         69%
        high value customers                                  31%



 More expensive communicatons to                                                          69%
       high value customers                             25%



   Media is diffferentiated based on                                            50%
       type of customer value                                             44%                   Postpaid:
                                                                                                Prepaid:



   Media is differentiated based on               19%
     predicted reason for churn        0%



        Do not use customer value           13%
        information to differentiate
        marketing communicatons                                                 50%




Figure 3.33     How operators are using customer value information                                          to
   differentiate marketing communications – Postpaid versus Prepaid

           •      Differentiated marketing communications for high value Postpaid
                  customers are quite widespread with over 50% of operators varying
                  their media to customers on this basis.
           •      Prepaid marketing communications are also differentiated by 50% of
                  operators and appear to be on the increase. Operators admitted
                  predominantly using SMS as a media to communicate to their high
                  value Prepaid customers. Many operators also run ongoing marketing
                  campaigns to incentives customers to provide their correct name and
                  mailing address to allow more rich media communications to these
                  customers.




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3.6.24 92% of operators in highly competitive markets use customer value
       information to differentiate marketing communications to Postpaid
       customers




      Offer differentiated based on                                                        92%
             customer value                                     50%



  More frequent communications to                                                 75%
        high value customers                                    50%



 More expensive communicatons to                                            67%
       high value customers                                                       75%   Med-High MCI
                                                                                        Low MCI


   Media is diffferentiated based on                                  58%
       type of customer value                     25%



   Media is differentiated based on         17%
     predicted reason for churn                   25%



        Do not use customer value      8%
        information to differentiate
        marketing communicatons                   25%




Figure 3.34     How operators are using customer value information to
   differentiate marketing communications – Postpaid and split by market
   competitiveness

           •      Majority of operators in high MCI markets offer differentiated offers,
                  more frequent and expensive communications to high value Postpaid
                  customers.




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3.6.25 69% of operators use churn propensity information to differentiate
       marketing communications to high value Postpaid customers


                                                                 44%
 Offer differentiated based on churn
           score and reason
                                       6%




                                                                 44%
  Communications sent based on a
     set churn score threshold
                                       6%


                                                                                        Postpaid:
                                                                                        Prepaid:



  Media is differentiated based on                         38%
 churn score (eg. Telem'ktg for high
       churn risk customers)                13%




       Do not use churn propensity                   31%
        information to differentiate
        marketing communicatons                                                   75%




Figure 3.35     How operators are using churn propensity information to
   differentiate marketing communications – Postpaid versus Prepaid

           •      Few operators are yet to differentiate marketing communications to
                  Prepaid customers based on churn propensity. Majority of operators
                  are testing churn propensity scoring on their Postpaid customer base
                  before rolling out to Prepaid customers.




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3.6.26 A much higher proportion of operators in medium to highly competitive
       markets are using churn propensity scoring to differentiate marketing
       communications to Postpaid customers with 83% vs. 25% respectively


                                                                         58%
  Communications sent based on a
     set churn score threshold
                                       0%




                                                                  50%
 Offer differentiated based on churn
           score and reason
                                                  25%


                                                                                        Med-High MCI
                                                                                        Low MCI



  Media is differentiated based on                          42%
 churn score (eg. Telem'ktg for high
       churn risk customers)                      25%




       Do not use churn propensity          17%
        information to differentiate
        marketing communicatons                                                   75%




Figure 3.36      How operators are using churn propensity information to
   differentiate marketing communications – Postpaid and split by market
   competitiveness

           •      Though not to the same level as medium to high MCI operators, one in
                  four operators in low MCI markets are using churn propensity data to
                  differentiate media and offers to Postpaid customers.




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3.6.27 Only operators in medium to highly competitive markets are using churn
       propensity scoring to differentiate marketing communications to Prepaid
       customers




       Do not use churn propensity                             67%
        information to differentiate
        marketing communicatons                                                     100%




  Media is differentiated based on               17%
 churn score (eg. Telem'ktg for high
       churn risk customers)           0%

                                                                     Med-High MCI
                                                                     Low MCI


                                            8%
 Offer differentiated based on churn
           score and reason
                                       0%




                                            8%
  Communications sent based on a
     set churn score threshold
                                       0%




Figure 3.37     How operators are using churn propensity information to
   differentiate marketing communications – Prepaid and split market
   competitiveness




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3.6.28 No operator in the study differentiates network access on call costs


                                                                              yes
 100%                                                                         no



  90%


  80%


  70%


  60%


  50%


  40%


  30%


  20%


  10%


  0%
                    Postpaid:                            Prepaid:



Figure 3.38  Percentage breakdown of whether operators are differentiating
   network access priority based on whether the call is a free or paid call

Emagine Point of View
Network prioritising to high value customers may not be possible on many GSM
and CDMA networks but things may be set to change with the introduction of
3rd Generation networks.
Emagine found that no operators have taken the step to displace low value
customers with high value customers when a cell is at capacity. All operators’
networks operated on a ‘first come’, ‘ first serve’ basis.
It appears that service differentiation based on value occurs at customer service
and marketing level, but not yet at the “core product” network level.
This could be a reflection that the majority of operators have a CRM focus
primarily driven through Customer Services and Marketing and are yet to extend
to all aspects of a customers experience.
Though not possible for many GSM and CDMA networks, the launch of 3rd
Generation networks (UMTS) may see a change. With certain 3G networks, it will
be possible to prioritise a customer’s network access based on customer value.
For example a low value customer may move from 128k to 16K-access speed to
accommodate a high value customer on the same node who will always
receive fastest access.




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Emagine believes there is an opportunity to operators to create a perceived
quality advantage by offering enhanced or optimum network quality to based
customer value – after all this customer interaction is in actually using the “core
product” of the operator, and is truly where value based differentiation should
begin.



3.6.29 Over 93% of operators make customer value segmentation data available
       to marketing, customer service and customer save
                                                                                    100.0%
    100.0%
                                                                                                      93.8%            93.8%

     90.0%


     80.0%


     70.0%


     60.0%                                                            56.3%

                                    50.0%
     50.0%


     40.0%

                                                    31.3%
     30.0%


     20.0%


     10.0%

                  0.0%
      0.0%
             Not available to   Front of House   Sales Indirect     Sales Direct   Marketing     Customer Service   Customer Save
              any division




Figure 3.39   Percentage breakdown of the divisions operators are making
   customer value segmentation information available to

       •     The study has found a high amount of operators (56%) are providing
             their direct sales force with customer value segmentation information
             and 31% are even providing this information to indirect sales channels.
       •     The trend of providing customer value segmentation information to an
             operators channels has been evident with many operators involving
             their sales channels in retention campaigns.
       •     Increasing market saturation and penetration also means more
             customers coming off contract and returning to their store for a
             handset upgrade.
       •     Many operators have information available to stores to gauge how
             high a handset subsidy a customer may be entitled to and to assist the
             recontracting of existing customers with relevant offers.



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3.6.30 Use Customer Contracts (Postpaid) or SIM Lock (Prepaid)


3.6.30.1 75% of operators use contracts for Postpaid, and 56% use SIM lock for
   Prepaid.




 100%

                                                                                                                    no
  90%                                                                                                               yes
                                25%

  80%
                                                                                          44%

  70%


  60%


  50%


  40%
                                75%

  30%
                                                                                          56%

  20%


  10%


  0%
        Do you use Customer contracts for postpaid handsets?           Do you use SIM locks for prepaid handsets?



Figure 3.40    Percentage breakdown of the use of customer contracts for
   Postpaid handsets and the use of SIM locks for Prepaid handsets


  Emagine point of view
  While SIM locks are a popular way of controlling churn, in some countries
  (mostly third world) it has become an ineffective strategy due to the
  proliferation of SIM unlock techniques available through the black-market. This
  has put pressure on Prepaid operators in these markets, as they are unable to
  reward high value Prepaid customers with increased handset subsidies.
  Consequently they have had to find other methods to retain their high value
  Prepaid base.




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3.6.31 Implement Re-Subsidisation and/or Handset Upgrade Programs


3.6.31.1 Handset subsidies are much greater for Postpaid than Prepaid
         customers


                                    $180.00
                                                                                                                         Postpaid
                                                                                                                         Prepaid
                                    $160.00          $152.72

                                                                                          $138.40
                                    $140.00
 Average Handset subsidy (US$PPP)




                                    $120.00


                                    $100.00


                                     $80.00
                                                                                                                $64.68
                                     $60.00                              $55.47



                                     $40.00


                                     $20.00


                                      $0.00
                                                           Acquisition                              Retention



Figure 3.41   Average handset subsidies for acquisition versus retention – split
   Postpaid versus Prepaid

                                         •    Handset subsidies are almost three times as much for acquiring
                                              Postpaid customers than for acquiring Prepaid customers. This is
                                              because a Postpaid customer can be locked in through a contract,
                                              thus ensuring that the operator will get their investment back. It also
                                              reflects the fact that few operators subsidise Prepaid handsets at all,
                                              precisely because they cannot be certain the customer will stay with
                                              the network.
                                         •    Postpaid customer handset subsidies for retention are almost $15 less
                                              on average than for acquisition subsidies.

                                    Emagine point of view
                                    Postpaid retention handset subsidies are lower than for acquisition as many
                                    retention managers have been unable to secure the budget to subsidise
                                    handsets, whereas their sales orientated counterparts have been able to
                                    obtain larger budgets.


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   Emagine believes that it is important to bring acquisition and retention
   handset subsidies in line with each other otherwise there is little incentive for
   the customer to recontract when they can get a better phone by either
   going to another network or disconnecting then reconnecting on the same
   network. Ultimately this costs the operator more money than if they just
   increased the handset subsidy for retention.
   Prepaid subsides for retention increase by an average of almost $10 from that
   paid for acquisition. This is due to operators beginning to target high value
   Prepaid customers. Operators recognise the commitment these customers
   have made to the network and reward them with a greater subsidy (and thus
   lower cost handset) than they would at acquisition when they are unsure of
   their commitment.



3.6.32     Implement Operational Customer Segmentation


3.6.32.1 Most Prepaid operators are not yet conducting customer value based
   segmentation




                                                                                            69%
      Average revenue/Rate plan based
                                                                 38%




                                                                                      63%         Postpaid:
              Tiered Gold/Silver/Bronze                                                           Prepaid:
                                                           31%




    Customer Lifetime net present value                                44%
                   (NPV)
                                                     25%




                                               19%
                    Contribution Margin
                                                     25%




                                          6%
     Not conducting value segmentation
                                                                       44%




Figure 3.42   Percentage breakdown of the use                                  of   customer       value
   segmentation methods – Postpaid versus Prepaid

(Note: Totals do not add as some operators run multiple segmentation models)



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        •      A large percentage (44%) of operators are not running any form of
               segmentation at all from their Prepaid customers, while only 6% of
               operators are not conducting Postpaid segmentation.
        •      Though least popular still one in five operators are running contribution
               margin segmentation for both Pre and Postpaid customers.



3.6.32.2       80% of high MCI operators are running customer value segmentation
               methods with 58% using average revenue/rate plan based
               segmentation followed by 50% using tiered Gold/Silver/Bronze forms of
               segmentation




                                                                                  58%
       Average revenue/Rate plan based
                                                              38%




                                                                         50%
               Tiered Gold/Silver/Bronze                                       Med-High MCI
                                                              38%              Low MCI




     Customer Lifetime net present value                      38%
                    (NPV)
                                                     25%




                                               21%
      Not conducting value segmentation
                                                              38%




                                               21%
                     Contribution Margin
                                                     25%




Figure 3.43   Percentage breakdown of the use of customer value
   segmentation methods for both Postpaid versus Prepaid – split by market
   competitiveness

        •      As one would expect High MCI operators are much more involved in
               the use of customer value segmentation methods the operators in less
               competitive markets.




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3.6.33 Implement Recontracting Offers


3.6.33.1    Churn significantly reduces when operators recontract their
   customers

                              3.00%

                                                                                               Avg Off Contract Churn (% mthly)
                                                                                               Avg On Contract Churn (% mthly)
                                                                                               Avg Recontract Churn (% mthly)
                                                           2.46%
                              2.50%




                              2.00%
 Monthly Postpaid Churn (%)




                              1.50%




                              1.00%
                                                                         0.80%




                              0.50%
                                                                                      0.37%




                              0.00%
                                                                        Overall:


Figure 3.44 Average off contract versus on contract and recontract churn
   comparison within the medium market competitiveness stage

                                      •   Average recontracted churn is significantly lower than for on contract
                                          churn (0.37% per month recontracted compared to 0.80% per month
                                          on the initial contract). This suggests that once issues such as pricing,
                                          handsets etc are removed from the equation, churn is very
                                          manageable. Therefore, implying that operators should aim to
                                          recontract as many customers as possible.
                                      •   On average there is a high level of off-contract churn (2.46%). As
                                          there is nothing to hold these customers to the carrier these customers
                                          are, therefore, essentially in the same category as Prepaid customers
                                          and thus can churn rapidly. The operator, however, has the
                                          opportunity to contain this churn by increasing their value to the
                                          customer by providing targeted offers.




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3.6.33.2 37% of operators have achieved or exceeded their objectives
         for re-contracting campaigns, whilst a further 25% are achieving
         partial objectives.


                        6%

                                     19%




        31%                                           No plans for program
                                                      Strategy under development
                                                      Implemented / achieving partial objectives
                                                      Implemented / meeting core objectives
                                                      Implemented / objectives met beyond expectations
                                            19%




                             25%




Figure 3.45    Percentage breakdown of the use of recontracting offers by
   operators and their effectiveness

Emagine point of view
This result suggests that once issues such as pricing, handsets etc are removed
from the equation, churn is very manageable. Operators should therefore aim to
recontract as many customers as possible.




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3.6.34 Implement Loyalty Programs


3.6.34.1 Far fewer operators offer rewards for Prepaid customers than for
        Postpaid




          Handset upgrades                                                                              75%
                                                      25%

             Special Events                                                           63%
                                                19%

     Accessories - batteries                                                  50%
                                          13%

              Movie tickets                                             44%
                                     6%

                   - car kits                                     38%                       Postpaid:
                                     6%
                                                                                            Prepaid:

                 - chargers                                       38%
                                     6%

              Free minutes                                        38%
                                                      25%

       - portable hands free                                31%
                                     6%

           Rental discounts                     19%
                                0%

                      Credit                    19%
                                     6%

             VAS discounts                13%
                                0%

                   Airmiles               13%
                                0%




Figure 3.46   Percentage breakdown of rewards offered by operators in their
   Postpaid and Prepaid loyalty programs


      •      Only 27% of operators are offering Prepaid reward programs, versus
             67% of operators who are offering Postpaid reward programs
      •      Operators who do offer Prepaid customers rewards, tend to confine
             the reward options to a narrow choice compared with those they offer
             Postpaid customers
      •      Most operators offer handset upgrades, tickets to special events, and
             battery accessories as rewards.
      •      Low MCI Postpaid operators tend to concentrate their reward offers
             on a few key products – handset upgrades, accessories, special
             events and movie tickets. In contrast operators from medium and high
             MCI markets provide a much broader choice of rewards for Postpaid
             customers.




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         •   For Prepaid the choice of rewards is substantially less than for Postpaid.
             Where Low MCI markets do offer Prepaid rewards they are confined to
             battery accessories, handset upgrades and free minutes. Most
             medium MCI companies also have a smaller selection of rewards than
             for Postpaid, however the range is broader than that of their low MCI
             counterparts.

3.6.35       Case Study – Loyalty Programs
   Customer Loyalty Program – Hong Kong CSL

   Introduction

   With 6 cellular operators, and 9 networks, Hong Kong is widely regarded as
   the most competitive market in the world for mobile services. Intense
   competition has contributed to historically high churn levels. Hong Kong was
   also one of the first markets in the world to introduce full Mobile Number
   Portability (MNP).

   Hong Kong CSL (formerly Hong Kong Telecom Mobile) holds a 20% market
   share , with a customer base of over 1,000,000 customers. Its share of market
   value is substantially higher at around 34%, illustrating its success in attracting
   and retaining higher value customers.

   Issue

   Given the competitive nature of the Hong Kong market, it comes as no
   surprise to learn that customer churn rates are amongst the highest in the
   world.

   HK CSL churn rates are considerably better than           the market average at
   around 3.4% in the consumer segment and 2.3% in           the premium high value
   segment. However, the company believes there              is still an opportunity to
   improve on this performance and recently set                about addressing this
   challenge.

   CSL was the first company in Hong Kong to employ a distinctive market
   segmentation strategy by marketing its services through three mobile brands:
   1010, One2Free, and "1+1" Communications. As a result CSL established a
   premium position in the Hong Kong market based on the promise of a
   superior network and innovative services. The success of this strategy is
   evident from CSL’s high share (34%) of total market value, delivered from its
   20% market share.

   CSL has concluded that a sustainable advantage at the high end of the
   market will only be achieved by providing fast to market innovation coupled
   with a recognizably superior level of service, for premium customers.




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  Having established a reputation for innovative services, CSL has more
  recently focused on differentiating the level of service it offers its premium
  1010 customers with the launch of Club Best 1010 – a unique loyalty scheme
  which the company recently introduced and made available exclusively to
  1010 customers.

  The Club Best 1010 program was launched in early April 2002 and represents
  CSL’s main effort to date, to distance itself from the competition, on the basis
  of ‘service privileges’.

  One of the key objectives of the marketing team was also to consolidate
  existing marketing retention spend, into a single coordinated “umbrella”
  program, that would be flexible enough to cater for the varied needs of CSL’s
  highly segmented, highly demanding customer base.

  Previously, some HK CSL Mobile high value customers also participated in the
  Hong Kong Telecom fixed-line Loyalty Program called the “No. 1 partners
  club”. This program had relatively low mobile specific retention value,
  however, it had previously been supported due to the importance of the
  program to the fixed line business. Approximately 20-30% of 1010 customers
  had been registered with this program.

  Recent changes in the corporate structure de-coupled the fixed and mobile
  businesses, giving HK CSL (Mobile) the opportunity to determine if this
  approach could be improved.

  Options explored and Solution implemented

  HK CSL created an innovative, proactive Customer Relationship
  Management (CRM) framework which would act as a key driver and trigger
  in transforming the business. The objective was to transform CSL’s reactive
  relationship management approach to a more proactive, intimate
  approach, developing the customer relationship throughout the customer
  lifecycle with CSL 1010.

  The mLoyalty Solution delivered by emagine International was to be an
  essential tool in creating value for customers. The customers interaction with
  this program needed to deliver more than might be achieved by simply
  offering customers a simple discount on their bill.

  In addition the requirement that this service should help to justify and re-
  enforce the service premium, additionally it needed to drive customer loyalty
  and potentially stimulate revenue growth in new service areas through
  flexible promotional offers of bonus reward points. The solution also had to be
  capable of being fully integrated with future complimentary products and
  services. It was important to ensure that the technology and surrounding
  processes had a much broader scope than a “simple Loyalty program”. If
  positioned and promoted well it could excite and educate customers about
  the online interactive nature of mobile telecommunications services.



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  This in turn would help to persuade many high value customers that by going
  ‘on-line’ they could benefit from an improved level of service management
  generally. If for example a customer could be persuaded to go on-line for
  the first time (by Web or WAP) to check his reward status, it would take only a
  small additional step to persuade him to access the ‘On-line assist’ account

  Service Launch and Key Features

  The ClubBest program was launched on April 7th 2002. 1010 customers were
  encouraged to register through a variety of initiatives:

  Personalised invitations to register with ClubBest were mailed out to all 200,000
  plus 1010 customers.

  SMS was used to explain eligibility to register free for the program. Individuals
  could respond immediately/briefly via SMS or via Web or WAP.

  In return for the completion of a more detailed profile over the web,
  customers received 50 bonus points

  Those who had previously registered with the “No 1 partners club” were
  invited to move their loyalty points over while registering for ClubBest.

  Initial reward points offered at registration ensured that all customers could
  immediately benefit from lower value rewards such as a free SMS allocation.

  For every Hong Kong Dollar of service expenditure appearing on the
  customer’s monthly bill, the customer is awarded one ClubBest point. Extra
  bonus points can be offered as part of particular promotions. A current
  promotion (May 2002) allows customers to benefit from 20% extra ClubBest
  points when roaming in mainland China.

  This initial offer represents a strategic attempt to overcome the trend for
  customers in the Hong Kong market who regularly roam to mainland China,
  to hold two SIMs, one with HKCSL and a second Prepay SIM with a local
  carrier on the mainland. This trend has hurt the Hong Kong carriers, including
  CSL. Margins on local calling in the Hong Kong market are relatively low due
  to the high levels of competition and a significant proportion of CSL’s profit
  margin depends on customer roaming revenues, particularly those
  generated by visitors to mainland China.

  Anniversary points are also offered for every year spent with 1010. These
  points increase dramatically over time. Points expire if unused within 2 years.

  A unique feature of the ClubBest program is the ability for 1010 customers to
  use their points to participate in a bidding auction for a range of new
  handsets. At the time of writing customers were invited to bid for a Sony
  Ericsson T68i with a minimum bid required of 3,888 points. A Nokia 6510 was
  also being auctioned with a minimum bid required of 1,888 points. Currently
  individual items, such as handsets are auctioned at the rate of one per week.



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   This feature has been particularly popular in the early weeks after the
  program launch.       Consequently, we may see more handsets being
  auctioned on a more regular basis, in the future.1010 customers are invited to
  redeem their points by exchanging them for a wide range of products and
  services, as well as mobile phone accessories, modem cards, Roaming and
  Prepay SIM cards and other more general gift items

  Results and lessons learned

  Since this mLoyalty solution was launched commercially quite recently (April
  2002), it is difficult to provide a comprehensive assessment of its impact.
  However, one of the key objectives of the ClubBest mLoyalty Program was to
  consolidate existing marketing retention spend, into a single coordinated
  “umbrella” program, that would be flexible enough to cater for the varied
  needs of CSL’s highly segmented, highly demanding customer base.

  Upon introduction of the program, HK CSL secured savings in its retention
  program by consolidating activities within the framework of this integrated
  loyalty program.

  The program has already proved to be self-funding simply through improved
  efficiency and cost savings via more effective customer retention spend.

  CSL does also expect increased customer revenues and a reduction in churn
  to result. However, it has not needed to factor in an improved return in these
  areas to justify its new mloyalty solution. Any result in these areas above and
  beyond the immediate efficiency and cost saving benefits, will be
  considered a bonus.

  CSL hopes to achieve a 1.5% increase in ARPU, attributable to the program.

  CSL also expects to achieve a reduction in churn as a consequence of this
  program. The exact impact remains to be seen but even a modest impact
  can have a significant impact on company profitability, given the
  concentration of high value customers within the 1010 base.

  The program has also been instrumental in encouraging customers to move
  towards online communication with CSL. The online nature of the program,
  with interaction encouraged via Web, Wap and IVR, has been effective in
  encouraging business customers, who often demand a high ‘touch’ personal
  service, to become- familiar with the advantages of mobile-specific channels
  in their daily contact with CSL.

  To facilitate this development, at launch, customers were provided with
  bonus points for completing online surveys, to encourage interaction via the
  web. Further encouragement has also been provided by inviting customers
  to sent to inform them, again reinforcing the interaction with CSL via the
  online medium.




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   An additional advantage to this multi-channel approach, rests in the fact
   that it encourages the most important CSL customers to move up the
   technological staircase, educating and encouraging them towards
   increased future mobile data usage.
   * Note: Operators mentioned in case studies are not necessarily participants in the
   study. This case study was independently provided courtesy of Prodata Partners Ltd.

3.6.36        Recharge Campaigns (Prepaid)


3.6.36.1 37% of operators have achieved or exceeded their objectives
         for Prepaid recharge campaigns, whilst a further 25% are
         achieving partial objectives




                            0%   6%




              31%                         19%


                                                     No plans for program
                                                     Strategy under development
                                                     Implemented / achieving partial objectives
                                                     Implemented / meeting core objectives
                                                     Implemented / objectives met beyond expectations




                                 44%




Figure 3.47   Percentage breakdown of the use of recharge campaigns –
   Prepaid and their effectiveness

         •   Majority of operators are conducting Prepaid customer recharge
             campaigns to stimulate the usage of their Prepaid customer base.
             Stimulation of usage for Prepaid customers through recharge
             campaigns is a growing strategy for mobile operators who have found
             the campaigns quite successful on a number of levels. Successful
             campaigns have increased the level or size of a customer’s average
             recharge and also reduced the average duration between recharges
             for customers.




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3.6.37         Migration Strategies for Prepaid and Postpaid


3.6.37.1 Only 6% of operators reported that a migration strategy for
         Prepaid to Postpaid had been successfully implemented and
         met or exceeded their core objectives for such a strategy




                            6%
                       0%




                                            31%



                                                       No plans for program
                                                       Strategy under development
                                                       Implemented / achieving partial objectives
                                                       Implemented / meeting core objectives
             38%
                                                       Implemented / objectives met beyond expectations




                                     25%




Figure 3.48    Percentage breakdown of the use of migration strategies –
   Prepaid to Postpaid and their effectiveness

         •     38% of operators have achieved partial success with Prepaid to
               Postpaid migration strategies
         •     In qualitative interviews many operators expressed a change of view
               with regards to Prepaid. Rather than trying to move customers from
               Prepaid to Postpaid, operators are increasingly treating Prepaid as
               simply another billing option. Rather than migrate customers, operators
               are focussing on treating high value Prepaid customers in a similar
               manner to equivalent Postpaid customers.




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3.6.38 56% of Operators have no plans for implementing a migration
      strategy for Postpaid to Prepaid




                      6%




          25%
                                               No plans for program
                                               Strategy under development
                                               Implemented / achieving partial objectives
                                               Implemented / meeting core objectives
                                               Implemented / objectives met beyond expectations

                                       56%




            6%



                 6%




Figure 3.49     Percentage breakdown of the use of migration strategies –
   Postpaid to Prepaid and their effectiveness

      •   The migration of Postpaid customers to Prepaid services is usually
          reserved as an option for credit challenged Postpaid customers.




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3.6.39 Offers – What Offers Actually Work to Reduce Customer Churn?


3.6.39.1 Retention offers that reduce the cost to the customer are the
         most effective at reducing churn

           Air time offers (eg free minutes)0%        13%                      38%                                    50%


                           Handset upgrade              19%       0%6%               31%                                44%


                    Contracts/Recontracting                 27%           0% 7%            27%                              40%


                     Rate plan optimisation             19%              13%           25%                      25%                      19%


                                    SIM lock                            47%                      7%     13%            20%                13%

                                                                                                                                                         Not applicable
                  Bill and / or call discounts    6%0%            25%                                   56%                                13%           Not effective
                                                                                                                                                         Average
                                                                                                                                                         Effective
      Migration offers - prepaid to postpaid                      40%                  7%                 33%                      13%         7%
                                                                                                                                                         Highly effective

New value-added services (e.g.mobile data
                 etc)
                                                      13%         13%                             56%                                    19%        0%


      Migration offers - postpaid to prepaid                       43%                      7%          21%                        29%              0%

    Third party offers (eg holidays, gift with
                   purchase)
                                                            25%                            44%                                    31%               0%

  Value added services for both network &
               non-network
                                                 5%                      41%                                  41%                         14%       0%


             Accessories (eg extra battery)                       38%                             31%                        25%               6%0%


                                             0%          10%      20%          30%   40%     50%        60%     70%         80%         90%      100%



Figure 3.50                            Percentage breakdown of the effectiveness of retention offers

                •        The top 4 retention offers are Airtime offers (e.g. free minutes), Handset
                         upgrades, Contracts/Recontracting, and Rate Plan Optimisation.
                •        The most effective retention offer is to provide free airtime with 50% of
                         operators stating that this is highly effective.
                •        Providing other offers that reduce the cost to the customer have also
                         been shown to be very effective. These include handset upgrades,
                         rate plan optimisation and billing or call discounts. All these offers have
                         the effect of reducing customers’ costs in some way and are far more
                         effective at churn reduction than providing other services (either third
                         party or the operators own.
                •        Recontracting customers is also an effective churn reduction tool with
                         44% of operators finding this highly effective. In chapter 3 it was shown
                         that recontracted churn is significantly lower (0.344% compared to
                         0.88%) than for on contract churn suggesting that once issues such as
                         pricing, handsets etc are removed from the equation, churn is very
                         manageable. Operators should therefore aim to recontract as many
                         customers as possible.



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4                                    Future of CRM


    4.1 Most medium to high MCI operators are expecting churn will not
        change substantially within 12 months


                                     6.00%



                                                                                                             Total monthly churn
                                     5.00%                                                                   Forecast Total monthly churn
      Total monthly churn rate (%)




                                     4.00%




                                     3.00%




                                     2.00%




                                     1.00%




                                     0.00%
                                             C         F   K   L   O        R         S          U   V   W         X          Y         AB

                                             Low MCI                         Med MCI                                               High MCI
                                                                       Avg forecast churn 1.9%


    Figure 4.1    Comparison of current total monthly churn rate versus forecasted
    churn rate in 12 months time

                                         •   Most medium to high MCI operators are not expecting churn to alter
                                             significantly in the next 12 months, suggesting that they have already
                                             brought churn down to what is considered an acceptable level.
                                         •   There is unlikely to be any major development in products or systems
                                             which would help operator’s further contain churn, however
                                             investment in systems and strategies to reduce churn will have an
                                             impact.
                                         •   It is expected that low MCI operator’s churn rates should reduce to a
                                             greater extent than Med/High MCI operators if they begin to
                                             implement churn management systems and processes and retention
                                             becomes a bigger priority.
                                         •
                                         •




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4.1.1   CRM Programmes of the future

Most operators today appear to have a fairly good grasp of customer usage
and demographics. While this may be sufficient to manage CRM today, as
markets increase in complexity, especially with the advent of data, and
channels multiply, greater customer knowledge will become a key differentiator
between operators in the future.

The seamless customer interaction with the operator at all touch points will
become critical. This entails being able to capture customer communication via
the web, email, POS to/from the mobile device(s), and other means, as well as
the traditional calls to customer care.

Furthermore, it requires operators to be proactive in gathering of information
rather than relying on the customer to advise the operator. The operator needs
to become more skilled at prompting the customer to update their information
and gathering information on customer preferences. This needs to be
undertaken not just through conventional means eg telemarketing but through
new channels, when and where the customer chooses.

To support these additional levels of information, systems now need to move
from being process driven to being true information based systems. This relies on
CRM systems being able to not only adequately capture all information but also
to process and present it in a way that is useful to different employees within the
organisation.

Finally, information needs to be shared amongst the company. Today most
customer information is available only to those who need to know i.e. customer
care, sales and marketing. The importance of service as a differentiating tool will
become more important in the new environment and every customer-facing
employee will require information to help him or her to “serve” the customer
rather than just make a sale or provide support.

There is a consensus between all operators in the study that operator channels to
market will play an ongoing and increasing role in an operators CRM strategy.
Many markets have achieved a high level of market penetration so the ‘new
acquisition only’ channels for customers are quickly becoming a thing of the
past. In order to survive existing channels have to start servicing existing
customers.




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4.1.2   Using existing channels to service customers



4.1.2.1 Direct Channels
Direct channels are increasingly becoming involved in the re-contracting of
existing customers. Operators understand the cost/benefit of re-contracting an
existing customer of a ‘known’ value, rather then focusing only on acquiring new
customers of an ‘unknown’ value. Because of this shift, the future of direct
channels remuneration of commissions, residuals, claw backs, and percentage
revenue, will have an equal weighting with new customers and with existing
customers being recontracted. In fact in some operations, it is already more
beneficial for direct channels to re-contract a high value customer rather then to
take on a new customer, particularly if renumerated on a percentage of
revenue for the customer.

Understanding an existing customer’s value at the channel level is still a major
problem in servicing existing customers. Operators already use direct-dial lines,
for use by direct channels, to their customer service call centres which authorise
the level of subsidy a customer may be entitled to, plus to help inform the
channel of any cross/up-sell opportunities for the customer that may be
available. Providing real time links to the channels existing systems on customer
value information will make this process much more seamless.

The other trend becoming more apparent is the ‘farming out’ or the allocation of
groups of customers to particular channels to take responsibility for the customer
relationship. Typically this has been isolated to low value customers or, in some
cases, high value SME customers who want a more personal experience. By
letting an operator’s channels focus on the low value customers (e.g. upgrades /
re-contract offers), this provides a better allocation of an operator’s resources to
focus more on high value customers.

Though still in the trial phase, many operators they expect this trend to continue
and even grow in the future.

4.1.2.2 Indirect channels
Though the trend in the industry is towards more consolidated direct channels,
indirect channels for operators will always have a place, particularly for Prepaid
services.

Many operators expect support for customers acquired through indirect
channels to grow through more direct channels, such as email, SMS, direct mail
and an operator’s website, which will be more involved in managing the
acquired customers lifecycle. Many operators have in place today systems and
campaigns to obtain more detailed customer information from indirect
channels.



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4.1.2.3 Operators website
The use of an operator’s website for customer handset upgrade and re-
contracting campaigns are being used very effectively by a great number of
operators in the study.

Though predominantly in the trial stage for many operators, this strategy is being
proclaimed a success due to the low cost to serve in implementing this proactive
retention strategy as a ‘self-managed’ customer process. There are also other
benefits in driving customers to an operator’s website in providing other positive
customer touch-points to promote new products and value added services.

Further to implementing proactive retention campaigns, an operator’s Website is
expected to play an increasing role in the collection of customer data and also
in communications to customers with HTML newsletters and special offers for
customers on an opt-in basis.

Some operators are also experimenting with providing customer help pages and
trouble shooting services via their website with ‘chat’ interfaces to customer
service representatives for tricky questions. This level of ‘self service’ is expected
to become critical with the launch of more complicated value added services,
and customer data applications to take the load of traditional customer service
channels.


4.1.2.4 Mobile Internet
The role of mobile Internet is also predicted to play a greater role in CRM in the
future but operators believe it will be a while before any real indication to what
level of involvement will be apparent. It is expected that customers will look to
their mobile Internet as their ‘portal’ to the operator and will expect to access a
level of service and content such as that already available on the operator’s
website.

The potential to personalise a customers experience with mobile Internet is
expected to evolve to a level much higher then available today – particularly as
a channel for new services.




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