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Learning from Experience, Simply

Marketing Science, Forthcoming

87 Pages Posted: 24 May 2012 Last revised: 8 Jan 2015

Song Lin

HKUST Business School

Juanjuan Zhang

Massachusetts Institute of Technology (MIT) - Sloan School of Management

John R. Hauser

MIT Sloan School of Management

Date Written: May 29, 2014


There is substantial academic interest in modeling consumer experiential learning. However, (approximately) optimal solutions to forward-looking experiential learning problems are complex, limiting their behavioral plausibility and empirical feasibility. We propose that consumers use cognitively simple heuristic strategies. We explore one viable heuristic - index strategies, and demonstrate that they are intuitive, tractable, and plausible. Index strategies are much simpler for consumers to use but provide close-to-optimal utility. They also avoid exponential growth in computational complexity, enabling researchers to study learning models in more-complex situations.

Well-defined index strategies depend upon a structural property called indexability. We prove the indexability of a canonical forward-looking experiential learning model in which consumers learn brand quality while facing random utility shocks. Following an index strategy, consumers develop an index for each brand separately and choose the brand with the highest index. Using synthetic data, we demonstrate that an index strategy achieves nearly optimal utility at substantially lower computational costs. Using IRI data for diapers, we find that an index strategy performs as well as an approximately optimal solution and better than myopic learning. We extend the analysis to incorporate risk aversion, other cognitively simple heuristics, heterogeneous foresight, and an alternative specification of brands.

Keywords: dynamic consumer learning, structural models, cognitive simplicity, index strategies, heuristics, multi-armed bandit problems, restless bandits, indexability

Suggested Citation

Lin, Song and Zhang, Juanjuan and Hauser, John R., Learning from Experience, Simply (May 29, 2014). Marketing Science, Forthcoming. Available at SSRN: or

Song Lin

HKUST Business School ( email )

Department of Marketing
Hong Kong
Hong Kong


Juanjuan Zhang

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

Cambridge, MA 02142
United States


John Hauser (Contact Author)

MIT Sloan School of Management ( email )

International Center for Research on the Mngmt Tech.
Cambridge, MA 02142
United States
617-253-2929 (Phone)
617-258-7597 (Fax)

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