Product launches with new attributes

a hybrid conjoint–consumer panel technique for estimating demand

Paul B. Ellickson, Mitchell J. Lovett, Bhoomija Ranjan

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The authors propose and empirically evaluate a new hybrid estimation approach that integrates choice-based conjoint with repeated purchase data for a dense consumer panel, and they show that it increases the accuracy of conjoint predictions for actual purchases observed months later. The key innovation lies in combining conjoint data with a long and detailed panel of actual choices for a random sample of the target population. By linking the actual purchase and conjoint data, researchers can estimate preferences for attributes not yet present in the marketplace, while also addressing many of the key limitations of conjoint analysis, including sample selection and contextual differences. Counterfactual product and pricing exercises illustrate the managerial relevance of the approach.
Original languageEnglish
Number of pages23
JournalJournal of Marketing Research
DOIs
Publication statusAccepted/In press - 2019

Keywords

  • Bayesian hierarchical models
  • choice models
  • conjoint
  • data fusion
  • predictive validity
  • revealed preference
  • stated preference

Cite this

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title = "Product launches with new attributes: a hybrid conjoint–consumer panel technique for estimating demand",
abstract = "The authors propose and empirically evaluate a new hybrid estimation approach that integrates choice-based conjoint with repeated purchase data for a dense consumer panel, and they show that it increases the accuracy of conjoint predictions for actual purchases observed months later. The key innovation lies in combining conjoint data with a long and detailed panel of actual choices for a random sample of the target population. By linking the actual purchase and conjoint data, researchers can estimate preferences for attributes not yet present in the marketplace, while also addressing many of the key limitations of conjoint analysis, including sample selection and contextual differences. Counterfactual product and pricing exercises illustrate the managerial relevance of the approach.",
keywords = "Bayesian hierarchical models, choice models, conjoint, data fusion, predictive validity, revealed preference, stated preference",
author = "Ellickson, {Paul B.} and Lovett, {Mitchell J.} and Bhoomija Ranjan",
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Product launches with new attributes : a hybrid conjoint–consumer panel technique for estimating demand. / Ellickson, Paul B. ; Lovett, Mitchell J.; Ranjan, Bhoomija.

In: Journal of Marketing Research, 2019.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Lovett, Mitchell J.

AU - Ranjan, Bhoomija

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AB - The authors propose and empirically evaluate a new hybrid estimation approach that integrates choice-based conjoint with repeated purchase data for a dense consumer panel, and they show that it increases the accuracy of conjoint predictions for actual purchases observed months later. The key innovation lies in combining conjoint data with a long and detailed panel of actual choices for a random sample of the target population. By linking the actual purchase and conjoint data, researchers can estimate preferences for attributes not yet present in the marketplace, while also addressing many of the key limitations of conjoint analysis, including sample selection and contextual differences. Counterfactual product and pricing exercises illustrate the managerial relevance of the approach.

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KW - choice models

KW - conjoint

KW - data fusion

KW - predictive validity

KW - revealed preference

KW - stated preference

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DO - 10.1177/0022243719843132

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