The DOI matches its Crossref record.
Impact of Sales Promotions on when, what, and how Much to Buy
Abstract
The effectiveness of a sales promotion can be examined by decomposing the sales “bump” during the promotion period into sales increase due to brand switching, purchase time acceleration, and stockpiling. The author proposes a method for such a decomposition whereby brand sales are considered the result of consumer decisions about when, what, and how much to buy. The impact of marketing variables on these three consumer decisions is captured by an Erlang-2 interpurchase time model, a multinomial logit model of brand choice, and a cumulative logit model of purchase quantity. The models are estimated with IRI scanner panel data for regular ground coffee. The results indicate that more than 84% of the sales increase due to promotion comes from brand switching (a very small part of which may be switching between different sizes of the same brand). Purchase acceleration in time accounts for less than 14% of the sales increase, whereas stockpiling due to promotion is a negligible phenomenon accounting for less than 2% of the sales increase.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Customer Switching Behavior in Service Industries: An Exploratory Study
Keaveney, S. M. (1995) · Journal of Marketing · doi:10.2307/1252074 · Cited by 2,905
Marketing Analytics for Data-Rich Environments
Wedel, M., & Kannan, P. K. (2016) · Journal of Marketing · doi:10.1509/jm.15.0413 · Cited by 1,261
A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy
Venkatesan, R., & Kumar, V. (2004) · Journal of Marketing · doi:10.1509/jmkg.68.4.106.42728 · Cited by 948
Kivetz, R., Urminsky, O., & Zheng, Y. (2006) · Journal of Marketing Research · doi:10.1509/jmkr.43.1.39 · Cited by 727
New Empirical Generalizations on the Determinants of Price Elasticity
Bijmolt, T. H. A., Van Heerde, H. J., & Pieters, R. G. M. (2005) · Journal of Marketing Research · doi:10.1509/jmkr.42.2.141.62296 · Cited by 440
Brand and Quantity Choice Dynamics Under Price Uncertainty
Erdem, T., Imai, S., & Keane, M. P. (2003) · Quantitative Marketing and Economics · doi:10.1023/a:1023536326497 · Cited by 331
Investigating Household Purchase Timing Decisions: A Conditional Hazard Function Approach
Jain, D. C., & Vilcassim, N. J. (1991) · Marketing Science · doi:10.1287/mksc.10.1.1 · Cited by 270
Customer Base Analysis: An Industrial Purchase Process Application
Schmittlein, D. C., & Peterson, R. A. (1994) · Marketing Science · doi:10.1287/mksc.13.1.41 · Cited by 248
Next-product-to-buy models for cross-selling applications
Knott, A., Hayes, A., & Neslin, S. A. (2002) · Journal of Interactive Marketing · doi:10.1002/dir.10038 · Cited by 161
The effects of mobile promotions on customer purchase dynamics
Park, C. H., Park, Y.-H., & Schweidel, D. A. (2018) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2018.05.001 · Cited by 51
Wu, C., & Chen, H.-L. (2000) · European Journal of Operational Research · doi:10.1016/s0377-2217(99)00326-4 · Cited by 35
Gender differences in customer behavioural responses to sales promotion
Ndubisi (2005) · Griffith Research Online · doi:10.6126/apmr.2005.10.3.03 · Cited by 6
Metadata
- Authors
- Gupta, S.
- Venue
- Journal of Marketing Research
- Publisher
- SAGE Publications
- Published
- 1988-11
- Volume
- 25
- Issue
- 4
- Pages
- 342-355
- ISSN
- 0022-2437 (ISSN-L)
- 1547-7193
- OpenAlex
- W1980671409
- Cited by
- 1,049
- References
- 0
- FWCI
- 53.71
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
