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An Optimal Contact Model for Maximizing Online Panel Response Rates

Author

Listed:
  • Scott A. Neslin

    (Tuck School of Business, Dartmouth College, Hanover, New Hampshire 03755)

  • Thomas P. Novak

    (A. Gary Anderson Graduate School of Management, University of California, Riverside, Riverside, California 92521)

  • Kenneth R. Baker

    (Tuck School of Business, Dartmouth College, Hanover, New Hampshire 03755)

  • Donna L. Hoffman

    (A. Gary Anderson Graduate School of Management, University of California, Riverside, Riverside, California 92521)

Abstract

We develop and test an optimization model for maximizing response rates for online marketing research survey panels. The model consists of (1) a decision tree predictive model that classifies panelists into "states" and forecasts the response rate for panelists in each state and (2) a linear program that specifies how many panelists should be solicited from each state to maximize response rate. The model is forward looking in that it optimizes over a finite horizon during which S studies are to be fielded. It takes into account the desired number of responses for each study, the likely migration pattern of panelists between states as they are invited and respond or do not respond, as well as demographic requirements. The model is implemented using a rolling horizon whereby the optimal solution for S successive studies is derived and implemented for the first study. Then, as results are observed, an optimal solution is derived for the next S studies, and the solution is implemented for the first of these studies, etc. The procedure is field tested and shown to increase response rates significantly compared to the heuristic currently being used by panel management. Further analysis suggests that the improvement was due to the predictive model and that a "greedy algorithm" would have done equally well in the field test. However, further Monte Carlo simulations suggest circumstances under which the model would outperform the greedy algorithm.

Suggested Citation

  • Scott A. Neslin & Thomas P. Novak & Kenneth R. Baker & Donna L. Hoffman, 2009. "An Optimal Contact Model for Maximizing Online Panel Response Rates," Management Science, INFORMS, vol. 55(5), pages 727-737, May.
    • Handle: RePEc:inm:ormnsc:v:55:y:2009:i:5:p:727-737
    DOI: 10.1287/mnsc.1080.0969
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    References listed on IDEAS

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    Cited by:

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    3. Aurélie Lemmens & Sunil Gupta, 2020. "Managing Churn to Maximize Profits," Marketing Science, INFORMS, vol. 39(5), pages 956-973, September.

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