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Modeling the effectiveness of hourly direct-response radio commercials

Author

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  • KIYGI CALLI, Meltem
  • WEVERBERGH, Marcel
  • FRANSES, Philip Hans

Abstract

The authors investigate the impact of direct-response commercials on incoming calls at a national call center. To this end, the authors analyze the data of a fast service for repairs of (parts of) a durable consumption good in Flanders, Belgium. The authors have access to data at the 15 minute interval covering 30 months in which 5172 radio commercials were broadcasted on six radio stations at various times of the day and at with differing commercial lengths. Their model is a two-level model, where the first-level estimates of the short-run and long-run effects are correlated with various aspects of the commercial in the second level. Their main conclusion is that GRPs are the key drivers of the effectiveness of commercials.

Suggested Citation

  • KIYGI CALLI, Meltem & WEVERBERGH, Marcel & FRANSES, Philip Hans, 2008. "Modeling the effectiveness of hourly direct-response radio commercials," Working Papers 2008005, University of Antwerp, Faculty of Applied Economics.
  • Handle: RePEc:ant:wpaper:2008005
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    References listed on IDEAS

    as
    1. Kamel Jedidi & Carl F. Mela & Sunil Gupta, 1999. "Managing Advertising and Promotion for Long-Run Profitability," Marketing Science, INFORMS, vol. 18(1), pages 1-22.
    2. Richard Paap & Philip Hans Franses, 2000. "A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 717-744.
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    5. Baghestani, Hamid, 1991. "Cointegration Analysis of the Advertising-Sales Relationship," Journal of Industrial Economics, Wiley Blackwell, vol. 39(6), pages 671-681, December.
    6. Philip Hans Franses & Richard Paap, 2011. "Random‐coefficient periodic autoregressions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 65(1), pages 101-115, February.
    7. Koen Pauwels & Shuba Srinivasan & Philip Hans Franses, 2007. "When Do Price Thresholds Matter in Retail Categories?," Marketing Science, INFORMS, vol. 26(1), pages 83-100, 01-02.
    8. Koen Pauwels & Shuba Srinivasan, 2004. "Who Benefits from Store Brand Entry?," Marketing Science, INFORMS, vol. 23(3), pages 364-390, July.
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    10. Tülin Erdem, 1996. "A Dynamic Analysis of Market Structure Based on Panel Data," Marketing Science, INFORMS, vol. 15(4), pages 359-378.
    11. Robert P. Leone, 1995. "Generalizing What Is Known About Temporal Aggregation and Advertising Carryover," Marketing Science, INFORMS, vol. 14(3_supplem), pages 141-150.
    12. Marnik G. Dekimpe & Dominique M. Hanssens, 1995. "The Persistence of Marketing Effects on Sales," Marketing Science, INFORMS, vol. 14(1), pages 1-21.
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    More about this item

    Keywords

    Advertising effectiveness; Two-level model; Advertising response; Long-run elasticity; Short-run effects;

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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