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  • November 2017
  • Teaching Note
  • HBS Case Collection

Predicting Consumer Tastes with Big Data at Gap

By: Ayelet Israeli and Jill Avery
  • Format:Print
  • | Language:English
  • | Pages:35
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Abstract

CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big data obtained from Google Analytics and the company's own sales and customer databases to select the next season's assortment. Peck was betting that intelligence fueled by big data could outperform a fashion industry creative director at predicting the future fashion trends and tastes of consumers.

Keywords

Brands; Brand & Product Management; Big Data; "Marketing Analytics"; Consumer Behavior; Predictive Analytics; Forecasting; Preferences; Operation Management; Distribution Channels; Marketing; Marketing Channels; Marketing Strategy; Brands and Branding; Forecasting and Prediction; Data and Data Sets; Retail Industry; Fashion Industry; Apparel and Accessories Industry; United States; North America

Citation

Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Teaching Note 518-053, November 2017.
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About The Authors

Ayelet Israeli

Marketing
→More Publications

Jill J. Avery

Marketing
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More from the Authors

    • March 2025
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    Unintended Consequences of Algorithmic Personalization

    By: Ayelet Israeli and Eva Ascarza
    • 2025
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    Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning

    By: Liangzong Ma, Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
    • October 2024
    • Journal of Marketing Research (JMR)

    Canary Categories

    By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
More from the Authors
  • Unintended Consequences of Algorithmic Personalization By: Ayelet Israeli and Eva Ascarza
  • Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning By: Liangzong Ma, Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
  • Canary Categories By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
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