How CRM is going to change the distribution sector in France

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HAL Id: hal-02520445

https://hal.archives-ouvertes.fr/hal-02520445

Submitted on 26 Mar 2020

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How CRM is going to change the distribution sector in

France

Jean-Louis Ermine, Daniel Lang, Philippe van Berten

To cite this version:

Jean-Louis Ermine, Daniel Lang, Philippe van Berten. How CRM is going to change the distribution sector in France. 4th Research Conference on Relationship Marketing and CRM, Nov 2007, Brussels, Belgium. �hal-02520445�

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6

1 Introduction

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3

2 CRM & Data Mining in the Marketing Literature

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2.1 Data Mining

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2.2 Variables

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2.2.1 Classification of the Variables

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2.2.2 Qualification of the variables

A = $ " % # , " ( $ % * $ + " " % # G $$ '( 0 0H M! 3 N % # " $$ ! # ' $$ # , A * + ( ! ! $' " % # ( " ' % $ % # # $$ , 1$ ( ' $ ' " ! # # #' + !BOO,,, # OD % O O" P% Q

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2.2.3 Suitable Variables for CRM

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2.3 Algorithms

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2.3.1 Descriptive Algorithms

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2.3.1.2 Market Basket Analysis

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2.3.2 Predictive Algorithms

2.3.2.1 Regression Analysis I - 5 0 ! * / ! - ! . 123 * / 5! ! / 123' - ! ! / 5

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- % " ! % $' " ! " " # , % # " " # $ % # # ! ! $ B " ( " 6& & ( , ( , ' T6+V 2 " % ! G $$ '( 0 0H M! 38NB ! ' " $ # $ % # 0 $ # , ! ' $ ! # % % # ' W " , ( + , " ! " G * $ H , # ' , ! # # $ $ 6 , ! $ " % $ ! % ' ! 0 $ $ % G % H !! $ ! ! , " , $ # " " G4 ' F . $$( 0 3H M! 338N ( , " ' " G4 ' F . $$( 0 3H M! 066N ( $ " " % # ( ( , $ $ % # + ! #' ' " % # , ! % " 9 ! A $ % # ( $ " ! ! ' # ( " $' I ! 5! ! * ! ! ! * ! J G? " A F ( 0 H 4 1 ) 5 ? " " :

DISTRIBUTION SECTOR & DATA MINING PROCESS

DEPENDENT VARIABLE VALUE

HOMOGENEOUS GROUPS OF customers, products, transaction…;

DESCRIPTIVE ALGORITHMS

PREDICTIVE ALGORITHMS STATISTICS

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0

2.4 CRM

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6

3 From Data Mining to CRM, a case study

3.1 First Project out of Proprietary Credit Card

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3.1.1 Methodology

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3.1.2 Released Model: a behavioral typology.

!+ 4 1 8 4 3 Basket – Multimedia −−−− House item −−−− Food + Purchases + Frequency + Clothes + Basket + Multimedia + House item + Purchases −−−− Frequency −−−− Clothes − Food −−− − Sizes of CL (cluster) proportionate the number of customers . > . : . 8 . . 6 . 3 . 0 . . &

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3 @ " $ G Z0 6 0H " % $ , " ( $ 6( , * # = ' .+ : ; 1 A 6 # ' U " & , 8 0[ # ' ' $ ! : [ ! 2 F / ! 1 ! ( = * " ! D " B I$! - ! * ! ! * ' / * / 'J , % ( " ! = ! % !! + " ; , " '! $ # % , ' = , + " " " + 95% of customers of green circled groups belongs to

Cluster 3 %Toys, Fitness %Toys, Fitness Exp.Toys, Fitness % Garden, Pets % Automobile % Garden, Pets Oth

C3 stands for « cluster Nr 3 » Oth stands for « others »

C3 3.7% 1221 Oth 96.3% 31498 Total 100% 32719 C3 3.7% 636 Oth 98.3% 31498 Total 100% 32060 C3 3.7% 1221 Oth 96.3% 31498 Total 100% 32719 C3 88.8% 585 Oth 11.2% 74 Total 100% 659 C3 1.1% 356 Oth 98.9% 31399 Total 100% 31755 C3 91.8% 280 Oth 8.2% 25 Total 100% 305 C3 72.3% 149 Oth 27.7% 57 Total 100% 206 C3 96.2% 436 Oth 3.8% 17 Total 100% 453 C3 0.7% 220 Oth 99.3% 31279 Total 100% 32499 C3 53.1% 136 Oth 46.9% 120 Total 100% 256 C3 72.3% 47 Oth 27.7% 18 Total 100% 65 C3 97.1% 233 Oth 2.9% 7 Total 100% 240 \ 0 83[ TS 0 83[ \ 0 >:[ TS 0> >:[ \ 6 66[ TS 6 66[ \ 0 [ TS 0 [ \ 6& [ _{T] 6&} _[

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3.2 Current Project out of loyalty card program

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8 " $ , ' ' # ' ! = ! G # 0H monthly expense June - 04 July - 04 Aug. - 04

Sept-04 Oct-04 Nov-04 Gold 484,2 442,5 437,2 456,7 454,2 477,6 Silver 179,6 186,7 183,2 191,2 197,4 199,9 Bronze 89,7 104,4 106,2 107,8 112,1 111,3 Switcher 36,7 48,2 53,0 55,3 58,6 59,7 Total store holder 253,8 230,1 223,6 242,7 239,1 247,9 Total holder exploitation 260,2 254,6 241,0 252,8 256,6 259,8 3 " + 4 8 4 "<< 1 = ( 8 4 3 8

% Card Holders expenses

Store Region

Business Income rate 54,4% 53,2%

Food purchase rate 59,3% 58,3%

Non Food purchase rate 44,9% 44,8%

comparison with previous month

3 ! 1 >1 3? 4 3 7 4

" 8 # , # #' " $ $ $ ' , ! # +

' ! ! $ " " ! ,

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4 The issue: Distribution, Marketing and CRM

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4.1 When Patronage is changing the rule: a new marketing model

in Distribution

@! ( ' " $ + ( $ ? ) ' F 4 , + , ) + " ) I3 /J( ! ( "' 1 $ ( = I3 /J , # B / G ( 0H M! &6N ' ' / # " ! + / ! ! ' , ' % / ! # = " ! $ ' ! " OPERATIONAL CRM ANALYTICAL CRM Channels Management Campaign Management Customer informations collect Customer informations analysis

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! $ I/ J $ , " " > 5 $ '( ' ' , " ! " , ! $ # $$ , # ( ! '( $ % $ $ + " # " ! + " # " 9 # , ; , " " I% ' ! % J ! $$ 5 " + , " ! % % " ! ' " ' # ' ! 9 ! , $ " ; , " # / ( + ! ! " . " $ $ # , # , '= ' $ " ! , # ( , " ! 9 , , , ! A "" ! $ I ; , " ! 'J # - # ( A B: C 3 PATRONS PURCHASERS MARKET KNOWLEDGE PROSPECTS CUSTOMER KNOWLEDGE PANELISTS ORGANISATION ENVIRONMENT

PATRONIZING DIRECT MARKETING

MARKETING CAMPAIGNS

MARKET STUDIES CUSTOMER KNOWLEDGE MGT

)) %

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4.2 Testing the model

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5 Conclusion

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00

6 References

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