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									 Trade Promotions and
   Pricing Strategies
           Vithala R. Rao
         Cornell University
Presentation at the 2006 AMA-Sheth
  Foundation Doctoral Consortium
           July 14, 2006
Trade Promotions and Pricing Strategies


   Two parts:
    1. An empirical study on budgeting and
      allocation of trade promotions

    2. A brief overview of pricing strategies
      adopted in three countries (USA,
      India and Singapore)
Empirical Analysis of Budget and
Allocation of Trade Promotions in the US
Supermarket Industry



               Miguel I. Gómez
                Vithala R. Rao
             Edward W. McLaughlin

               Cornell University
      Background

Increasing role of trade promotions

 • Spending:                     $(US) 8 billion in 1990 versus
                                 $(US) 80 billion in 2005

 • Share in marketing spending: 25% in 1980 versus
                                65-70% in 2003

 • Share of supplier sales:      6% in 1978 versus
                                 17% in 2003

 • Regulation:                   Not subject to regulation in
                                1980 versus FASB rule in 2001
Motivations


   Manufacturer
       Counter store brands
       Target price sensitive consumer
       Enhance brand
       Move inventory
       Counteract competitors
   Retailer
       Builds traffic, sales, margins
       Manufacturer bears cost (and risk)
 Literature Review—Selected Studies
             Study                Type                                Contribution/Finding
Curhan & Kopp (1986)          Empirical      Key factors to ensure retailer support for trade deals

Lal (1990)                    Theoretical    Off invoices and bill-back can help suppliers increase profits

Neslin, Powell and Stone      Empirical      Influence of retailer and consumer responses to manufacturer’s optimal
(1995)                                       advertising and trade promotion strategy

Ailawadi, Farris and Shames   Theoretical    Performance-based contracts yield higher returns to manufacturers over
(1999)                                       EDLP retailer strategies
Kasulis, Morgan, Griffith &   Theoretical    Relative market power between suppliers and retailers is a major force
Kenderdine (1999)                            driving negotiation of trade deals
Kumar, Rajiv and Jeuland      Theoretical    Strategic considerations determine retailer’s decision to pass through
(2001)                                       trade deals to consumers
Sullivan (2002)               Theoretical    Analysis of trade promotion contracts can help address policies related
                                             to antitrust enforcement
Hamilton (2003)               Theoretical    Slotting allowances can coordinate channel activity, increase supplier
                                             sales and improves consumer welfare

Dreze and Bell (2003)         Theoretical/   If terms of contracts are same, manufacturers prefer scan-backs while
                              Empirical      retailers prefer off invoice allowances
Srinivasan, Pauwels,          Empirical      Factors affecting the profitability of trade promotions for manufacturers
Hanssens Dekimpe (2004)                      and retailers; the impact on manufacturer revenues is positive but on
                                             retailer revenues is mixed
Besanko, Dubé and Gupta       Empirical      Pass-through varies substantially across product categories and strong
(2004)                                       evidence of asymmetric retailer response to trade promotions on large
                                             versus small brands
Literature Review: Main Findings

   Summary of extant literature
       Mostly theoretical, limited number of empirical studies
       Emphasis on pass-through
       Difficult to make generalizations
       Access to data is a constraint

   We employ a unique data set to examine the factors
    that affect outcomes of trade promotions
       Budget: trade promotion funds given by a manufacturer of a
        brand to a particular retailer
       Allocation: (1) off-invoices; (2) scan-backs and accruals; (3)
        bill-backs; (4) others
   Conceptual Model




Three possible negotiation processes
 • Budget defined first; then negotiate allocation
 • Allocation defined first; then negotiate budget (“top-down”
 approach)
 • Budget and allocation are determined jointly
      Model Comparisons
         Variable                 Joint       Top-Down         Objective-and-
                                               (Budget         Task (Allocation
                                                first)              first)

Budget (R-square)                    --            0.16                0.17

Allocation (Pseudo-R-                --            0.35                0.26
square)
Overall measure (average)          0.29            0.26                0.22



  Joint model: QLIM for all five variables
  Budget first: OLS for budget and QLIM for the allocation
  Allocation first: QLIM for the four allocations; budget as single equation.
                  Model Comparisons
   Specificatio    Equation      Position     Price   Manufact   Manufact   Retaile   Retailer   Private    Retail
   n                                        Premium     urer       urer     r Sales    Policy     Label    Branding
                                                       Sales      Policy                         Share
   Budget          Budget           +          -         -         NA         +         NA         -          -
   first,          Off invoice      -          -         -          -         +         +          +          +
   allocations     Accruals         +          -         +         +          -          -         -          +
   second          and scan
                   backs
                   Bill backs       +         +          -          +          -        +          -          -
                   Others           -         -          -          +          -        -*         +          +
   Allocations     Budget           +          -         -         NA         +         NA         -          -
   first, budget   Off invoice      -          -         -          -         +         +          +          +
   second          Accruals         +          -         +         +          -          -         -          +
                   and scan
                   backs
                   Bill backs       +         +          -          +          -         +         -          -
                   Others           -         -          -          +          -         +         +          +
   Budget and      Budget          +           -         -         NA         +         NA         +*         -
   allocations     Off invoice      -          -         -          -         +         +          +          +
   joint           Accruals        -*          -         +         +          -          -          -         +
                   and scan
                   backs
                   Bill backs       +         +          -          +          -         +         -          -
                   Others           -         -          -          +          -         +         +          +

NA: Not applicable; see text for the specification. * indicates exceptions
           Hypotheses: Manufacturer Characteristics

      Operational Measures             Budget   Allocatio   Allocation to   Allocation
                                                n to Off-     Accrual/       to Bill-
                                                invoices    Scan-backs        backs

Manufacturer Annual Sales - Total
manufacturer sales in 2002               -          -            +              +

Brand Position – 1 if leading or
second brand in retailer’s product       -          -            +              +
category; zero if growing brand

Price Premium - Price per unit of
volume minus the average price in        -          -            +              +
the product category divided by
average price in the product
category

Manufacturer Policy – 1 if              NA          -            +              +
manufacturer has formal policies for
the allocation of trade promotion
dollars; zero otherwise
    Hypotheses: Retailer Characteristics

     Operational Measures               Budget   Allocatio    Allocation   Allocation
                                                 n to Off-        to        to Bill-
                                                 invoices      Accrual/      backs
                                                             Scan-backs
Retailer Annual Sales - Total
manufacturer sales in 2002                +         +             -            -

Retail Branding – Index ranging
from 0-100 with consumer ratings          +         +             -            -
of supermarket companies

Share of Private Label – Share of
private label in product category                                 -            -
sales in 2002
                                          +         +

Retailer Policy – 1 if retailer has
formal policies for the allocation of    NA         +             -            -
trade promotion dollars; zero
otherwise
          Selection of Product Categories

   Each company provided data for two product categories from a total of five:
    ready-to-eat cereal, frozen dinners/entrees, coffee, laundry detergent and
    pet food

   Differ according to perishability, frequency of purchase, price level, cost of
    storage, and purchase ―intensity‖

   2004 IRI data on 25 categories to assess the representativeness of sample
        Average discount: 25 percent the five in our sample versus 23 percent the other
         twenty
        Percent of units sold on promotion were 37 and 35 percent for our five
         categories and for the other twenty, respectively
         Data Collection: Retailer Survey
   Intensive survey completed by 36 supermarket companies—40% of
    US sales (2003)
        Detailed data on 170 brands


   Dependent Variables:

         Trade Promotion Budget: Our budget measure is the amount of promotional
         dollars received from a manufacturer to the brand sales of the retailer in 2002

        Allocation of Trade Promotions: Percent allocated to (1) off-invoices; (2)
         scan-backs and accruals; (3) bill-backs; and (4) others in 2002



• Share of private label in product category sales and formal
policy for negotiation of allocation
         Data Collection


   Primary data on prices in various markets to calculate price differentials
    across brands

   Secondary data:
        Manufacturer sales, retailer sales from trade publications
        Retail branding from Consumer Reports (2003),

   Unique incentive: scholarship to two-week executive program (value
    $7,000)
            The Joint Model
                            Budget: y1,ijk  R ijk β1  M ljk α 1   1 Z j   1,ij   1,ijk
      Allocation to off-invoices: y 2,ijk  R ijk β 2  M ljk α 2   2 Z j   2,ij   2,ijk
                                    *


Alloc. to accruals/scan-backs: y 3,ijk  R ijk β 3  M ljk α 3   3 Z j   3,ij   3,ijk
                                 *


        Allocation to bill-backs: y 4,ijk  R ijk β 4  M ljk α 4   4 Z j   4,ij   4,ijk
                                    *


            Allocation to Others: y 5,ijk  R ijk β 5  M ljk α 5   5 Z j   5,ij   5,ijk
                                    *




             yn  yn,ijk if yn,ijk  0 and
                             *
                                               yn  0 if yn,ijk  0
                                                          *
                                                                       for n  2, 3, 4, 5,

 Where,
 i, l, j, k represent retailer, manufacturer, product category and brand, respectively
Rijk = [annual sales, share of private label in product category sales, retailer branding]
Mljk = [annual sales, brand price premium, brand position in product category sales]
Zj = [dummy variables for coffee, ready-to-eat cereal, laundry detergent, frozen dinners].
         Technical Issues
•     Budget equation suffers from possible ambiguity due to
      reverse causality

•     Error structure takes the form εn, ij + εn,ijk (n = 1, 2, 3, 4, 5)

•     The vector of error terms (ε1,ijk, ε2,ijk, ε3,ijk, ε4,ijk, ε5,ijk) has
      multivariate normal distribution with mean 0 and variance-
      covariance matrix Σ

•     In each equation we include the random error component
      εn,ij (n = 1, 2, 3, 4, 5) to reflect the possible
      heteroscedastic nature of our data; assume that the
      means are zero and
    E( )  f (RSi 1n , Z j γ 2n )   (1  exp(RSi 1n  Z j γ 2n ))
        2
        n,ij
                                         2
                                         n
    Estimation Method

   QLIM procedure in SAS, which accounts for the
    censored and continuous endogenous variables.

   Monte Carlo integration procedures to compute the
    multivariate integrations of the system of equations.

   Method of simulated scores (MSS) shown to be
    consistent and asymptotically normal.
    Determinants of Trade Promotion Budget



             Explanatory Variables                  Coefficient
         Intercept                             15.700***        (3.072)a
         Brand Position                        0.976***         (0.266)
         Price Premium                         -4.415***        (1.504)
         Manufacturer Sales                     -0.018          (0.012)
         Retailer Sales                        0.039**          (0.015)
         Share Private Label                    0.191           (4.949)
         Retail Branding                        -0.043          (0.042)
         Standard Error                        1.101***         (0.393)
         Pseudo R-squared                                0.17



aRobust Standard Errors; * significant at the 10 percent level; ** significant
at the 5 percent level; *** significant at the 1 percent level.
        Determinants of Allocation

    Dependent Variable:     Allocation to Off-Invoices         Allocation to Accruals
                                                                  And Scan-Backs

Explanatory Variables       Coefficient         Marginal     Coefficient        Marginal
                                                 Effect                          Effect

Intercept                 -1.428 (0.963)            --      0.018 (1.708)           --

Brand Position            -0.031 (0.063)          -0.030   -0.032 (0.070)         0.001

Price Premium             -0.255 (0.423)          -0.149   -0.040 (0.456)        -0.028

Manufacturer Sales        -0.002 (0.003)          -0.001   0.005* (0.002)         0.003

Manufacturer Policy       -0.249** (0.120)        -0.224   0.004     (0.118)     -0.020

Retailer Sales            0.007*** (0.002)        0.006    -0.001 (0.004)        -0.001

Share Private Label       2.446*** (0.950)        1.802    -1.525** (0.645)      -1.181

Retail Branding           0.016     (0.011)       0.006    0.006     (0.014)      0.005

Retailer Policy            0.025 (0.083)          0.040    -0.170* (0.104)       -0.185

Standard Error            0.246** (0.152)           --     0.236*** (0.046)         --
Pseudo R-squared                  0.40              --             0.20             --
        Determinants of Allocation

    Dependent Variable:        Allocation to Bill-Backs       Allocation to “Other” Types

Explanatory Variables       Coefficient           Marginal     Coefficient        Marginal
                                                   Effect                          Effect
Intercept                 2.018** (0.901)             --     0.134     (0.321)       --
Brand Position            0.067     (0.065)         0.029    -0.012    (0.025)     -0.002

Price Premium             0.190     (0.331)         0.126    -0.008    (0.114)     -0.035

Manufacturer Sales        -0.002    (0.002)        -0.001    -0.001    (0.001)     -0.001

Manufacturer Policy       0.258*** (0.110)          0.228    0.046      (0.039)    0.048

Retailer Sales            -0.005** (0.003)         -0.004    -0.004*** (0.001)     -0.003

Share Private Label       -1.462*** (0.569)        -1.108    0.584**    (0.184)    0.491

Retail Branding           -0.022* (0.012)          -0.019    0.011*     (0.006)    0.007

Retailer Policy           0.132*     (0.079)        0.170    0.011      (0.034)    0.006

Standard Error            0.293*** (0.058)            --     0.130*** (0.013)        --
Pseudo R-squared                  0.17                --             0.25            --
   Summary of Findings



• Trade promotion budget is negatively related to price premium,
manufacturer sales and the position of the brand in the product
category; and positively related to retailer sales

• Allocation to off-invoices increases with such retailer characteristics
as share of private label and retailer size; and decreases with
manufacturer formal policies

• Allocation to accruals and scan-backs decreases with such retailer
characteristics as share of private label and formal policy; and
increases with manufacturer size
 Summary of Findings



• Allocation to bill-backs decreases with such retailer characteristics
as share of private label, retail branding and retailer size; and
increases with manufacturer formal policies

• Allocation to other types increases with such retailer characteristics
as share of private label and retail branding; and decreases retailer
size
       Conclusions

   Trade promotions are influenced by characteristics of: retailer and
    manufacturer

   Trade promotion decisions appear to be jointly determined

   Neither supermarket companies nor grocery manufacturers have a
    dominant position in the negotiation of trade promotions
         Conclusions

   Trade promotions will likely remain contentious due to inherent buyer-seller
    conflict in goals

   Public policy needs to account for the characteristics here that determine
    trade promotion and allocation—helps to explain channel conduct

        eg, does the apparent ability of larger retailers to influence promotional
         allocation toward Off-Invoices result in larger consumer discounts?
       Future Research
   Collect additional data to identify product category characteristics that
    affect outcomes

   Game theoretic models and strategies to improve channel coordination

   Consider the inter-temporal relationships between budget and allocation

   Links between trade promotions and diverting

   Conduct comparable study across countries
Comparison of Pricing Strategies
       across Countries

 Survey on Pricing Strategies conducted in the
          US, India, and Singapore

     Vithala R. Rao and Benjamin Kartono
      Pricing Strategy Objectives

Objective of pricing strategy                    Mean Importance (5-point scale)

                                               US     Singapore    India    Sample
1. Increase or maintain sales volume           4.16      4.17       4.14      4.16
2. Increase or maintain market share           4.21      4.02       4.15      4.14
3. Increase or maintain gross profit margin    3.88      4.15       3.88      3.95
4. Increase or maintain sales revenue          4.12      4.00       3.72      3.94
5. Increase or maintain money gross profit     3.72      4.02       3.86      3.85
6. Cover costs                                 3.57      3.69       3.44      3.56
7. Project a desired product image             3.57      3.96       3.21      3.55
8. Maintain level of competition               3.42      3.54       3.18      3.36
9. Achieve rational price structure            3.06      3.33       2.93      3.09
10. Match competitor pricing                   2.85      3.19       3.07      3.02


(Top 10 pricing strategy objectives in decreasing order of the sample’s mean importance)
     Pricing Strategies: Mean % Importance

Pricing strategy                   US       Singapore        India       Sample


1. Cost-plus pricing              41.5          35.1          35.9         37.8
2. Parity pricing                 35.5          26.6          43.2         36.9
3. Perceived value pricing        34.3          32.8          27.9         33.1
4. Leader pricing                 35.0          17.1          32.5         30.5
5. Low-price supplier             27.5          28.0          32.0         29.3
6. Penetration pricing            25.8          23.0          33.3         27.4
7. Experience curve pricing       21.1          32.0          30.6         27.0
8. Price bundling                 26.3          27.2          20.5         25.4
9. Price skimming                 22.5          32.8          21.5         25.3
10. Break-even pricing            23.0          22.5          27.5         24.7

 (Top 10 pricing strategies in decreasing order of the sample’s mean % importance.
 The firms were asked to select up to 5 different pricing strategies and distribute
 100 percentage points among them)
         Pricing Strategy Determinants:
         Market Conditions

Market Conditions                      Ratings Scale       US     S’pore   India   Sample

1. Sensitivity of customers to price   1 = Insensitive,
                                                           4.92    4.85    4.66     4.81
   differences between brands          7 = Sensitive

2. Sensitivity of market demand        1 = Insensitive,
                                                           3.85    4.54    4.00     4.09
   to changes in average price         7 = Sensitive

3. Ease of determining market          1 = Difficult,
                                                           3.86    4.04    4.34     4.08
   demand                              7 = Easy
4. Market growth rate                  1 = Low, 7 = High   3.92    4.00    4.54     4.16
5. Customer switching costs            1 = Low, 7 = High   3.21    3.94    3.65     3.56
6. Customer search costs               1 = Low, 7 = High   3.21    3.68    3.06     3.28
7. Customer transaction costs          1 = Low, 7 = High   2.96    3.47    3.21     3.18
8. Impact of the internet on market
                                       1 = Low, 7 = High   2.15    2.48    1.38     1.98
   demand
9. Legal constraints                   1 = Low, 7 = High   2.48    2.28    2.06     2.27

								
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