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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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