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Marketing Research
 Rags Srinivasan




Customer Segmentation and
Market Share Estimation With
Conjoint Analysis
Marketing is about segmentation and
targeting
                       Nothing more strategic than segmentation




Cannot treat the                      Value proposition is        Target them
                                                                  differently – SKUs,
whole market as                       different for each
one                                   segment                     messaging



  Rags Srinivasan IterativePath.com
What defines a segment?
  Internally homogenous, externally
  heterogeneous
Is your segmentation valid?




                                     Meaningful, relevant and
 Not too small, Not too
                                     intuitively identified by
 large
                                     constituent variables




 Rags Srinivasan IterativePath.com
Conjoint analysis helps you with the
clustering




          Premise: The whole is the sum of its parts.
            We can infer the relative importance of
          parts from the customer preference of the
                            whole.




 Rags Srinivasan IterativePath.com
For Example
Assign a value between 1 and 100 to these options. 100 means most
likeable and 1 means least likeable




 Price: $2499                        Price: $799        Price: $1999
 Screen: 50”                         Screen: 42”        Screen: 42”
 Display: LCD                        Display: Plasma    Display: LCD


 Rags Srinivasan IterativePath.com
Conjoint analysis helps identify clusters



                                     Brand conscious

                                     Price Sensitive

                                     Screen size

                                     Display type




 Rags Srinivasan IterativePath.com
… and relative importance of attributes




 What is the utility value a customer assigns to each
 attribute?




 Rags Srinivasan IterativePath.com
But you cannot ask customers about every
combination

        Use commercial software to generate a manageable set of profiles




                                      Conjoin
                                                 Manageabl
                                         t
Attributes              Levels                    e set of          Survey
                                      Softwar
                                                  profiles
                                       e




  Rags Srinivasan IterativePath.com
Let Us Walk Through An Example: My Work
On Airline Unbundled Pricing
 Questions: How much do airline customers value services like free-
 baggage, free drinks etc? Are airlines better off increasing ticket price
 instead of unbundling pricing?




   SFO                                                            JFK
With Following Options …


3 Airlines   2 Price         Extras for Baggage, Pillows and Soft-
             levels: $275,   drinks
             $250
Created 8 Profiles For Measuring Customer
Utility




Brand: 3 levels                     A manageable set of 8
Price: 2 levels                     profiles that stand-in for
                         Software
Baggage Fees: 2 levels              all variable
Pillow Fees: 2 levels               combinations
Drink Fee: 2 levels
Survey customers to find their utility value
for each profile
  Rate your likelihood of choosing the option on a scale of 1 – 10 ( 8 profiles)
Model: Utility = f(Brand, Price,Fees)
 Write customer utility (their likelihood of picking the airline) as a linear
 function of these variables

     U = Constant + b1 * JetBlue + b2* Delta + b3* Price$275 +
     b4* BaggageFee$20 + b5 * PillowFee$4 +b6 * DrinkFee$2


    JetBlue and Delta are mutually exclusive – 1 or 0
    AA is implicitly defined when both JetBlue and Delta are 0


    Price$275 = 1 means price is $275 , if it is 0 the price is $250
    So on and so forth

    b1, b2, … are the regression coefficients that are the relative
    utilities of attributes that we seek to find
Use SPSS to indentify clusters




    This margin is too narrow to contain it. Stay tuned I will add a
    Camtasia demo of using SPSS to do Cluster analysis and
    Regression.




 Rags Srinivasan IterativePath.com
Run multiple regression for each cluster to
find the coffecients

                         U = 8.36 + 0.88 * JetBlue – 0.06 * Delta – 1.9 * Price$275 –
 If we did not
                         2.41 * BaggageFee$20 – 0.83 * PillowFee$4 – 0.79 *
 cluster
                         DrinkFee$2



                          U = 7.9 + 1.28 * JetBlue – 0.16 * Delta – 2.34 * Price$275 –
  Cluster 1
                          3.14 * BaggageFee$20 – 0.92* PillowFee$4 – 0.87 *
                          DrinkFee$2



                         U = 8.6 + 0.4 * JetBlue + 0.17 * Delta – 1.24 * Price$275 –
 Cluster 2
                         1.68 * BaggageFee$20 – 0.63* PillowFee$4 – 0.58 *
                         DrinkFee$2


 Rags Srinivasan IterativePath.com
You can see the difference between two
clusters
  JetBlue, $250, Baggage Fee $20, Pillow Fee $4, Drink Fee $2




                          Cluster 1          Cluster 2
       JetBlue            9.18               9
       $250               0                  0
       Baggage Fee $20 -3.14                 -1.68
       Pillow Fee $4      -0.92              -0.63
       Drink Fee $2       -0.87              -0.58
       Total Utility      4.25               6.11
Compute market share from the
utility values of the brands


                                              Market
       Utility
                                              Share
    of Product i
                                           of Product i


                                   
                                  Ui
                   MS i             
                            U1 U 2 U 3




                                                      Feb 11, 2009
The net of this is



   When you want to segment customers and target them with
   multiple SKUs you need to do cluster analysis

   Conjoint analysis gets you there and more

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A Simple Tutorial on Conjoint and Cluster Analysis

  • 1. Marketing Research Rags Srinivasan Customer Segmentation and Market Share Estimation With Conjoint Analysis
  • 2. Marketing is about segmentation and targeting Nothing more strategic than segmentation Cannot treat the Value proposition is Target them differently – SKUs, whole market as different for each one segment messaging Rags Srinivasan IterativePath.com
  • 3. What defines a segment? Internally homogenous, externally heterogeneous
  • 4. Is your segmentation valid? Meaningful, relevant and Not too small, Not too intuitively identified by large constituent variables Rags Srinivasan IterativePath.com
  • 5. Conjoint analysis helps you with the clustering Premise: The whole is the sum of its parts. We can infer the relative importance of parts from the customer preference of the whole. Rags Srinivasan IterativePath.com
  • 6. For Example Assign a value between 1 and 100 to these options. 100 means most likeable and 1 means least likeable Price: $2499 Price: $799 Price: $1999 Screen: 50” Screen: 42” Screen: 42” Display: LCD Display: Plasma Display: LCD Rags Srinivasan IterativePath.com
  • 7. Conjoint analysis helps identify clusters Brand conscious Price Sensitive Screen size Display type Rags Srinivasan IterativePath.com
  • 8. … and relative importance of attributes What is the utility value a customer assigns to each attribute? Rags Srinivasan IterativePath.com
  • 9. But you cannot ask customers about every combination Use commercial software to generate a manageable set of profiles Conjoin Manageabl t Attributes Levels e set of Survey Softwar profiles e Rags Srinivasan IterativePath.com
  • 10. Let Us Walk Through An Example: My Work On Airline Unbundled Pricing Questions: How much do airline customers value services like free- baggage, free drinks etc? Are airlines better off increasing ticket price instead of unbundling pricing? SFO JFK
  • 11. With Following Options … 3 Airlines 2 Price Extras for Baggage, Pillows and Soft- levels: $275, drinks $250
  • 12. Created 8 Profiles For Measuring Customer Utility Brand: 3 levels A manageable set of 8 Price: 2 levels profiles that stand-in for Software Baggage Fees: 2 levels all variable Pillow Fees: 2 levels combinations Drink Fee: 2 levels
  • 13. Survey customers to find their utility value for each profile Rate your likelihood of choosing the option on a scale of 1 – 10 ( 8 profiles)
  • 14. Model: Utility = f(Brand, Price,Fees) Write customer utility (their likelihood of picking the airline) as a linear function of these variables U = Constant + b1 * JetBlue + b2* Delta + b3* Price$275 + b4* BaggageFee$20 + b5 * PillowFee$4 +b6 * DrinkFee$2 JetBlue and Delta are mutually exclusive – 1 or 0 AA is implicitly defined when both JetBlue and Delta are 0 Price$275 = 1 means price is $275 , if it is 0 the price is $250 So on and so forth b1, b2, … are the regression coefficients that are the relative utilities of attributes that we seek to find
  • 15. Use SPSS to indentify clusters This margin is too narrow to contain it. Stay tuned I will add a Camtasia demo of using SPSS to do Cluster analysis and Regression. Rags Srinivasan IterativePath.com
  • 16. Run multiple regression for each cluster to find the coffecients U = 8.36 + 0.88 * JetBlue – 0.06 * Delta – 1.9 * Price$275 – If we did not 2.41 * BaggageFee$20 – 0.83 * PillowFee$4 – 0.79 * cluster DrinkFee$2 U = 7.9 + 1.28 * JetBlue – 0.16 * Delta – 2.34 * Price$275 – Cluster 1 3.14 * BaggageFee$20 – 0.92* PillowFee$4 – 0.87 * DrinkFee$2 U = 8.6 + 0.4 * JetBlue + 0.17 * Delta – 1.24 * Price$275 – Cluster 2 1.68 * BaggageFee$20 – 0.63* PillowFee$4 – 0.58 * DrinkFee$2 Rags Srinivasan IterativePath.com
  • 17. You can see the difference between two clusters JetBlue, $250, Baggage Fee $20, Pillow Fee $4, Drink Fee $2 Cluster 1 Cluster 2 JetBlue 9.18 9 $250 0 0 Baggage Fee $20 -3.14 -1.68 Pillow Fee $4 -0.92 -0.63 Drink Fee $2 -0.87 -0.58 Total Utility 4.25 6.11
  • 18. Compute market share from the utility values of the brands Market Utility Share of Product i of Product i  Ui MS i     U1 U 2 U 3 Feb 11, 2009
  • 19. The net of this is When you want to segment customers and target them with multiple SKUs you need to do cluster analysis Conjoint analysis gets you there and more