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Market segmentation with choice-based conjoint analysis

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Abstract

Choice-based conjoint analysis has increased in popularity in recent years among marketing practitioners. The typical practice is to estimate choice-based conjoint models at the aggregate level, given insufficient data for individual-level estimation of part-worths. We discuss a method for market segmentation with choice-based conjoint models. This method determines the number of market segments, the size of each market segment, and the values of segment-level conjoint part-worths using commonly collected conjoint choice data. A major advantage of the proposed method is that current (incomplete) data collection approaches for choice-based conjoint analysis can still be used for market segmentation without having to collect additional data. We illustrate the proposed method using commercial conjoint choice data gathered in a new concept test for a major consumer packaged goods company. We also compare the proposed method with ana priori segmentation approach based on individual choice frequencies.

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References

  1. Bozdogan, H. (1987). “Model Selection and Akaike's Information Criterion: The General Theory and its Analytical Extensions.”Psychometrika, 52, 345–370.

  2. DeSarbo, W.S., M. Wedel, M. Vriens, and V. Ramaswamy. (1992). “Latent Class Metric Conjoint Analysis.”Marketing Letters, 1992, 273–288.

  3. Elrod, T., J.J. Louviere, and K.S. Davey. (1992). “An Empirical Comparison of Ratings-Based and Choice-Based Conjoint Models.”Journal of Marketing Research, 29 (August), 368–377.

  4. Green, P.E., and A.M. Krieger. (1991). “Segmenting Markets with Conjoint Analysis.”Journal of Marketing, 55 (October), 20–31.

  5. Green, P.E., and K. Helsen. (1989). “Cross-Validation Assessment of Alternatives to Individual-Level Conjoint Analysis: A Case Study.”Journal of Marketing Research, 26, 346–350.

  6. Gupta, S., and P.K. Chintagunta. (1994). “On Using Demographic Variables to Determine Segment Membership in Logit Mixture Models.”Journal of Marketing Research, 31, 128–136.

  7. Johnson, R. (1992).Sawtooth Software: The CBC System. Evanston, IL: Sawtooth.

  8. Kamakura, W.A., and G.J. Russell. (1989). “A Probabilistic Choice Model for Market Segmentation and Elasticity Structure.”Journal of Marketing Research, 26, 379–390.

  9. Louviere, J.J., and G.G. Woodworth. (1983). “Design and Analysis of Simulated Choice or Allocation Experiments: An Approach Based on Aggregate Data.”Journal of Marketing Research, 20, 350–367.

  10. Moore, W.M. (1980). “Levels of Aggregation in Conjoint Analysis: An Empirical Comparison.”Journal of Marketing Research, 17, 516–523.

  11. Ramaswamy, V., and W.S. DeSarbo. (1990). “SCULPTRE: A New Methodology for Deriving and Analyzing Hierarchical Product-Market Structures from Panel Data.”Journal of Marketing Research, 27 (November), 418–427.

  12. Ramaswamy, V., W.S. DeSarbo, D.J. Reibstein, and W.T. Robinson. (1993). “An Empirical Pooling Approach for Estimating Marketing Mix Elasticities with PIMS Data.”Marketing Science, 12(1) (Winter), 103–124.

  13. Struhl, S. (1994). “Discrete Choice Modeling: Understanding a ‘Better Conjoint than Conjoint.’”Quirk's Marketing Research Review, 8, 6, 12+.

  14. Wedel, M. and W.S. DeSarbo. (1994). “A Review of Recent Developments in Latent Class Regression Models,” inAdvanced Methods of Marketing Research, R.P. Bagozzi (ed.), 352–388. Cambridge, MA: Blackwell.

  15. Wittink, D.R., and P. Cattin. (1989). “Commercial Use of Conjoint Analysis: An Update.”Journal of Marketing, 53, 91–96.

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Desarbo, W.S., Ramaswamy, V. & Cohen, S.H. Market segmentation with choice-based conjoint analysis. Marketing Letters 6, 137–147 (1995). https://doi.org/10.1007/BF00994929

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Key words

  • Choice experiments
  • conjoint analysis
  • market segmentation