The DOI matches its Crossref record.
The Effects of Free Sample Promotions on Incremental Brand Sales
Abstract
The authors present a model of free sample effects and evidence from two field experiments on free samples. The model incorporates three potential effects of free samples on sales: (1) an acceleration effect, whereby consumers begin repeat purchasing of the sampled brand earlier than they otherwise would; (2) a cannibalization effect, which reduces the number of paid trial purchases of the brand; and (3) an expansion effect, which induces purchasing by consumers who would not consider buying the brand without a free sample. The empirical findings suggest that, unlike other consumer promotions such as coupons, free samples can produce measurable long-term effects on sales that can be observed as much as 12 months after the promotion. The data also show that the effectiveness of free sample promotions can vary widely, even between brands in the same product category. Application of the model to the data from the two experiments reveals that the magnitude of acceleration, cannibalization, and expansion effects varies substantially across the two free sample promotions. These and other findings suggest that the model can be a useful tool for obtaining insights into the nature of free sample promotions.
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
Effects of Freemium Strategy in the Mobile App Market: An Empirical Study of Google Play
Liu, C. Z., Au, Y. A., & Choi, H. S. (2014) · Journal of Management Information Systems · doi:10.1080/07421222.2014.995564 · Cited by 274
Hamari, J., Hanner, N., & Koivisto, J. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2016.09.004 · Cited by 177
How do firms make money selling digital goods online?
Lambrecht, A., Goldfarb, A., Bonatti, A., Ghose, A., Goldstein, D. G., Lewis, R., Rao, A., Sahni, N., & Yao, S. (2014) · Marketing Letters · doi:10.1007/s11002-014-9310-5 · Cited by 167
Wang, Q., Li, B., & Singh, P. V. (2018) · Information Systems Research · doi:10.1287/isre.2017.0735 · Cited by 162
Economics of Free Under Perpetual Licensing: Implications for the Software Industry
Niculescu, M. F., & Wu, D. J. (2014) · Information Systems Research · doi:10.1287/isre.2013.0508 · Cited by 151
The implications of offering free versions for the performance of paid mobile apps
Arora, S., ter Hofstede, F., & Mahajan, V. (2017) · Journal of Marketing · doi:10.1509/jm.15.0205 · Cited by 127
Kharrazi, H., Gonzalez, C. P., Lowe, K. B., Huerta, T. R., & Ford, E. W. (2018) · Journal of Medical Internet Research · doi:10.2196/10458 · Cited by 84
Foubert, B., & Gijsbrechts, E. (2016) · Marketing Science · doi:10.1287/mksc.2015.0973 · Cited by 72
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
The challenge of retaining customers acquired with free trials
Datta, H., Foubert, B., & Van Heerde, H. J. (2015) · Journal of Marketing Research · doi:10.1509/jmr.12.0160 · Cited by 22
Freemium Pricing: Evidence from a Large-scale Field Experiment
Runge, J., Wagner, S., & Claussen, J. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2888471 · Cited by 9
Metadata
- Authors
- Bawa, K., & Shoemaker, R.
- Venue
- Marketing Science
- Published
- 2004-08
- Volume
- 23
- Issue
- 3
- Pages
- 345-363
- ISSN
- 0732-2399 (ISSN-L)
- 1526-548X
- OpenAlex
- W1969045005
- Cited by
- 271
- References
- 0
- FWCI
- 13.12
- 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.