Skip to main content

Sales Promotion Effectiveness: The Impact of Category – Brand Level Price Promotions on Sales Performance of a Large Retailer

  • Conference paper
  • First Online:
Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation (INFUS 2021)

Abstract

Sales promotion is a primary tool included in the marketing mix that can arbitrate the sales trend. Retailers need to deploy business analytics to measure and define key performance indicators to determine an accurate measurement of return in investment for individual promotions. In this context, the need for an advanced Decision Support System (DSS) to orchestrate promotion strategy is critical for the companies. A brand-level model, which will assess promotional performances of brands within the category, could provide a helpful tool to retailers both for category management and price promotions activity allocation. This research estimates promotion/sales elasticity models for 11 brand-category groups to assess promotion efficiency using the ARDL bounds test method. Brand-level model, we estimated points that own price and promotion depth effect have the most significant impact magnitude on sales. Auto-regressive Distributed Lag type models we employed for this analysis enable us to differentiate long- and short-term analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Andersen, E.T., Simester, D.I.: Long-run effects of promotion depth on new versus established customers: three field studies. Mark. Sci. 23(1), 4–20 (2004). https://doi.org/10.1287/mksc.1030.0040

    Article  Google Scholar 

  2. Anderson, E.T., Fox, E.J.: How price promotions work: a review of practice and theory. In: Dubé, J.P., Rossi, P.F. (eds.) Handbook of the Economics of Marketing, vol. 1, chap. 9, pp. 497–552, 1 edn. North Holland, Amsterdam (2019). https://doi.org/10.1016/bs.hem.2019.04.006

  3. Association, A.M.: Definition of marketing (2017). https://www.ama.org/the-definition-of-marketing-what-is-marketing/

  4. Bell, D.R., Chiang, J., Padmanabhan, V.: The decomposition of promotional response: an empirical generalization. Mark. Sci. 18(4), 504–526 (1999). http://www.jstor.org/stable/193240

    Article  Google Scholar 

  5. Gupta, S.: Impact of sales promotions on when, what, and how much to buy. J. Mark. Res. 25(4), 342–355 (1988)

    Article  Google Scholar 

  6. van Heerde, H.J., Neslin, S.A.: Sales promotion Models. In: Wierenga, B., van der Lans, R. (eds.) Handbook of Marketing Decision Models, vol. 254, chap. Sales Prom, pp. 13–77. Springer, Cham, internatio edn. (2017). https://doi.org/10.1007/978-3-319-56941-32

  7. Klein, L.R.: The estimation of distributed lags. Econometrica 26(4), 553–565 (1958). https://doi.org/10.2307/1907516. http://www.jstor.org/stable/1907516

    Article  MathSciNet  MATH  Google Scholar 

  8. Koyck, L.M.: Distributed Lags and Investment Analysis. North-Holland Publishing Company, Amsterdam (1954)

    Google Scholar 

  9. Leeflang, P.S., Parreño Selva, J., Van Dijk, A., Wittink, D.R.: Decomposing the sales promotion bump accounting for cross-category effects. Int. J. Res. Mark. 25(3), 201–214 (2008). https://doi.org/10.1016/j.ijresmar.2008.03.003

    Article  Google Scholar 

  10. Parsons, L.J., Schultz, R.L.: Marketing Models and Econometric Research. North Holland, Amsterdam (1976)

    MATH  Google Scholar 

  11. Pesaran, M.H., Shin, Y., Smith, R.J.: Bounds testing approaches to the analysis of level relationships. J. Appl. Econom. 16(3), 289–326 (2001). https://doi.org/10.1002/jae.616

    Article  Google Scholar 

  12. Van Heerde, H.J., Gupta, S., Wittink, D.R.: Is 75% of the sales promotion bump due to brand switching? No, only 33% is. J. Mark. Res. 40(4), 481–491 (2003)

    Article  Google Scholar 

  13. Varian, H.R.: A model of sales. Am. Econ. Rev. 70(4), 651–659 (1980)

    Google Scholar 

  14. Zellner, A.: An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. J. Am. Stat. Assoc. 57(298), 348–368 (1962). https://doi.org/10.1080/01621459.1962.10480664. https://www.tandfonline.com/doi/abs/10.1080/01621459.1962.10480664

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ömer Zeybek .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zeybek, Ö., Ülengin, B. (2022). Sales Promotion Effectiveness: The Impact of Category – Brand Level Price Promotions on Sales Performance of a Large Retailer. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A.C., Sari, I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 307. Springer, Cham. https://doi.org/10.1007/978-3-030-85626-7_107

Download citation

Publish with us

Policies and ethics