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A simple tutorial to show conjoint analysis and cluster analysis. please send your feedback, this version is still rough and I would like to iteratively improve it so it is useful for most.
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Marketing ResearchRags Srinivasan
Customer Segmentation and Market Share Estimation With Conjoint Analysis
Marketing is about segmentation and targeting
Rags Srinivasan IterativePath.com
Cannot treat the whole market as one
Nothing more strategic than segmentation
Value proposition is different for each segment
Target them differently – SKUs, messaging
What defines a segment?
Internally homogenous, externally heterogeneous
Is your segmentation valid?
Rags Srinivasan IterativePath.com
Not too small, Not too large
Meaningful, relevant and intuitively identified by constituent variables
Conjoint analysis helps you with the clustering
Rags Srinivasan IterativePath.com
Premise: The whole is the sum of its parts. We can infer the relative importance of parts from the
customer preference of the whole.
For Example
Rags Srinivasan IterativePath.com
Price: $2499Screen: 50”Display: LCD
Price: $799Screen: 42”Display: Plasma
Price: $1999Screen: 42”Display: LCD
Assign a value between 1 and 100 to these options. 100 means most likeable and 1 means least likeable
Conjoint analysis helps identify clusters
Rags Srinivasan IterativePath.com
Brand conscious
Price Sensitive
Screen size
Display type
… and relative importance of attributes
Rags Srinivasan IterativePath.com
What is the utility value a customer assigns to each attribute?
But you cannot ask customers about every combination
Rags Srinivasan IterativePath.com
Use commercial software to generate a manageable set of profiles
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 levels: $275, $250
Extras for Baggage, Pillows and Soft-drinks
Created 8 Profiles For Measuring Customer Utility
Brand: 3 levelsPrice: 2 levelsBaggage Fees: 2 levelsPillow Fees: 2 levelsDrink Fee: 2 levels
SoftwareA manageable set of 8 profiles that stand-in for all variable combinations
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 0AA is implicitly defined when both JetBlue and Delta are 0
Price$275 = 1 means price is $275 , if it is 0 the price is $250So 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
Rags Srinivasan IterativePath.com
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.
Run multiple regression for each cluster to find the coffecients
Rags Srinivasan IterativePath.com
If we did not cluster
U = 8.36 + 0.88 * JetBlue – 0.06 * Delta – 1.9 * Price$275 – 2.41 * BaggageFee$20 – 0.83 * PillowFee$4 – 0.79 * DrinkFee$2
Cluster 1 U = 7.9 + 1.28 * JetBlue – 0.16 * Delta – 2.34 * Price$275 – 3.14 * BaggageFee$20 – 0.92* PillowFee$4 – 0.87 * DrinkFee$2
Cluster 2 U = 8.6 + 0.4 * JetBlue + 0.17 * Delta – 1.24 * Price$275 – 1.68 * BaggageFee$20 – 0.63* PillowFee$4 – 0.58 * DrinkFee$2
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
Feb 11, 2009
Compute market share from the utility values of the brands
Utilityof Product
i
Market Share
of Product i
321 UUU
UMS i
i
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