IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v64y2022ics0969698921003751.html
   My bibliography  Save this article

Predicting future consumer purchases in grocery retailing with the condensed Poisson lognormal model

Author

Listed:
  • Trinh, Giang
  • Wright, Malcolm J.

Abstract

To identify the effect of marketing actions on consumer purchasing, analysts must disentangle the dynamic component of purchasing from expected period-to-period stochastic fluctuations. This is done by comparing marketplace observations to the conditional expectation of future purchasing. Current methods of deriving the conditional expectation contain systematic bias and rely on certain unrealistic modelling assumptions. We therefore propose a new model to predict future consumer purchases in grocery retailing. The new model is a mixture of Erlang-2, Poisson and lognormal distributions or a condensed Poisson lognormal model (CPLN). Using two grocery retailing datasets from the UK, we demonstrate that the CPLN model predicts future consumer purchases well with error of 7% and 9%, respectively. Compared with the previous benchmark model, the condensed Negative Binominal Distribution (CNBD), the CPLN model reduces error by 50% (7% versus 14%) and 67% (9% versus 27%), respectively. Theoretical and practical implications for retailers are discussed.

Suggested Citation

  • Trinh, Giang & Wright, Malcolm J., 2022. "Predicting future consumer purchases in grocery retailing with the condensed Poisson lognormal model," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:joreco:v:64:y:2022:i:c:s0969698921003751
    DOI: 10.1016/j.jretconser.2021.102809
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698921003751
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jretconser.2021.102809?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fred S. Zufryden, 1978. "An Empirical Evaluation of a Composite Heterogeneous Model of Brand Choice and Purchase Timing Behavior," Management Science, INFORMS, vol. 24(7), pages 761-773, March.
    2. David C. Schmittlein & Albert C. Bemmaor & Donald G. Morrison, 1985. "Technical Note—Why Does the NBD Model Work? Robustness in Representing Product Purchases, Brand Purchases and Imperfectly Recorded Purchases," Marketing Science, INFORMS, vol. 4(3), pages 255-266.
    3. Giang Trinh & Cam Rungie & Malcolm Wright & Carl Driesener & John Dawes, 2014. "Predicting future purchases with the Poisson log-normal model," Marketing Letters, Springer, vol. 25(2), pages 219-234, June.
    4. Abel P. Jeuland & Frank M. Bass & Gordon P. Wright, 1980. "A Multibrand Stochastic Model Compounding Heterogeneous Erlang Timing and Multinomial Choice Processes," Operations Research, INFORMS, vol. 28(2), pages 255-277, April.
    5. Martin, James & Nenycz-Thiel, Magda & Dawes, John & Tanusondjaja, Arry & Cohen, Justin & McColl, Bruce & Trinh, Giang, 2020. "Fundamental basket size patterns and their relation to retailer performance," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    6. Trinh, Giang & Khan, Huda & Lockshin, Larry, 2020. "Purchasing behaviour of ethnicities: Are they different?," International Business Review, Elsevier, vol. 29(4).
    7. A. S. C. Ehrenberg, 1959. "The Pattern of Consumer Purchases," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 8(1), pages 26-41, March.
    8. C Wu & H-L Chen, 2000. "A consumer purchasing model with learning and departure behaviour," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(5), pages 583-591, May.
    9. Uncles, Mark D. & Ehrenberg, Andrew S. C. & Goodhardt, Gerald J., 2004. "Reply to commentary on "Understanding brand performance measures: using Dirichlet benchmarks"," Journal of Business Research, Elsevier, vol. 57(12), pages 1329-1330, December.
    10. Jerome Herniter, 1971. "A Probablistic Market Model of Purchase Timing and Brand Selection," Management Science, INFORMS, vol. 18(4-Part-II), pages 102-113, December.
    11. Kenneth Train ., 2000. "Halton Sequences for Mixed Logit," Economics Working Papers E00-278, University of California at Berkeley.
    12. Trinh, Giang & Corsi, Armando & Lockshin, Larry, 2019. "How country of origins of food products compete and grow," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 231-241.
    13. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    14. Rainer Winkelmann, 2008. "Econometric Analysis of Count Data," Springer Books, Springer, edition 0, number 978-3-540-78389-3, December.
    15. Sorensen, Herb & Bogomolova, Svetlana & Anderson, Katherine & Trinh, Giang & Sharp, Anne & Kennedy, Rachel & Page, Bill & Wright, Malcolm, 2017. "Fundamental patterns of in-store shopper behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 37(C), pages 182-194.
    16. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    17. David Hensher, 2001. "The valuation of commuter travel time savings for car drivers: evaluating alternative model specifications," Transportation, Springer, vol. 28(2), pages 101-118, May.
    18. Wu, Couchen & Chen, Hsiu-Li, 2000. "Counting your customers: Compounding customer's in-store decisions, interpurchase time and repurchasing behavior," European Journal of Operational Research, Elsevier, vol. 127(1), pages 109-119, November.
    19. Kaas, R. & Hesselager, O., 1995. "Ordering claim size distributions and mixed Poisson probabilities," Insurance: Mathematics and Economics, Elsevier, vol. 17(2), pages 193-201, October.
    20. Morrison, Donald G & Schmittlein, David C, 1988. "Generalizing the NBD Model for Customer Purchases: What Are the Implications and Is It Worth the Effort?," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 145-159, April.
    21. Anesbury, Zachary William & Talbot, Danielle & Day, Chanel Andrea & Bogomolov, Tim & Bogomolova, Svetlana, 2020. "The fallacy of the heavy buyer: Exploring purchasing frequencies of fresh fruit and vegetable categories," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    22. Desmond Lam & Richard Mizerski, 2009. "An investigation into gambling purchases using the NBD and NBD–Dirichlet models," Marketing Letters, Springer, vol. 20(3), pages 263-276, September.
    23. Ehrenberg, Andrew S. C. & Uncles, Mark D. & Goodhardt, Gerald J., 2004. "Understanding brand performance measures: using Dirichlet benchmarks," Journal of Business Research, Elsevier, vol. 57(12), pages 1307-1325, December.
    24. Donald G. Morrison & David C. Schmittlein, 1981. "Predicting Future Random Events Based on Past Performance," Management Science, INFORMS, vol. 27(9), pages 1006-1023, September.
    25. Morrison, Donald G & Schmittlein, David C, 1988. "Generalizing the NBD Model for Customer Purchases: What Are the Implications and Is It Worth the Effort? Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 165-166, April.
    26. Fred S. Zufryden, 1977. "A Composite Heterogeneous Model of Brand Choice and Purchase Timing Behavior," Management Science, INFORMS, vol. 24(2), pages 121-136, October.
    27. Page, Bill & Trinh, Giang & Bogomolova, Svetlana, 2019. "Comparing two supermarket layouts: The effect of a middle aisle on basket size, spend, trip duration and endcap use," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 49-56.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giang Trinh & Cam Rungie & Malcolm Wright & Carl Driesener & John Dawes, 2014. "Predicting future purchases with the Poisson log-normal model," Marketing Letters, Springer, vol. 25(2), pages 219-234, June.
    2. Trinh, Giang & Corsi, Armando & Lockshin, Larry, 2019. "How country of origins of food products compete and grow," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 231-241.
    3. Anesbury, Zachary William & Talbot, Danielle & Day, Chanel Andrea & Bogomolov, Tim & Bogomolova, Svetlana, 2020. "The fallacy of the heavy buyer: Exploring purchasing frequencies of fresh fruit and vegetable categories," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    4. Trinh, Giang & Khan, Huda & Lockshin, Larry, 2020. "Purchasing behaviour of ethnicities: Are they different?," International Business Review, Elsevier, vol. 29(4).
    5. Trinh, Giang, 2014. "Predicting variation in repertoire size with the NBD model," Australasian marketing journal, Elsevier, vol. 22(2), pages 111-116.
    6. Reutterer, Thomas & Platzer, Michael & Schröder, Nadine, 2021. "Leveraging purchase regularity for predicting customer behavior the easy way," International Journal of Research in Marketing, Elsevier, vol. 38(1), pages 194-215.
    7. Mizerski, Richard & Mizerski, Katherine & Lam, Desmond & Lee, Alvin, 2013. "Gamblers' habit," Journal of Business Research, Elsevier, vol. 66(9), pages 1605-1611.
    8. Trinh, Giang & Lam, Desmond, 2016. "Understanding the attendance at cultural venues and events with stochastic preference models," Journal of Business Research, Elsevier, vol. 69(9), pages 3538-3544.
    9. Zhiqiang (Eric) Zheng & Peter Fader & Balaji Padmanabhan, 2012. "From Business Intelligence to Competitive Intelligence: Inferring Competitive Measures Using Augmented Site-Centric Data," Information Systems Research, INFORMS, vol. 23(3-part-1), pages 698-720, September.
    10. Nenycz-Thiel, Magda & Beal, Virginia & Ludwichowska, Gosia & Romaniuk, Jenni, 2013. "Investigating the accuracy of self-reports of brand usage behavior," Journal of Business Research, Elsevier, vol. 66(2), pages 224-232.
    11. Meade, Nigel & Islam, Towhidul, 2010. "Using copulas to model repeat purchase behaviour - An exploratory analysis via a case study," European Journal of Operational Research, Elsevier, vol. 200(3), pages 908-917, February.
    12. Shi, Ruixia & Chen, Hongyu & Sethi, Suresh P., 2019. "A generalized count model on customers' purchases in O2O market," International Journal of Production Economics, Elsevier, vol. 215(C), pages 121-130.
    13. Martin, James & Nenycz-Thiel, Magda & Dawes, John & Tanusondjaja, Arry & Cohen, Justin & McColl, Bruce & Trinh, Giang, 2020. "Fundamental basket size patterns and their relation to retailer performance," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    14. Trinh, Giang & Dawes, John, 2020. "A comparison of brand loyalty between on the go and take-home consumption purchases," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    15. Jeongwen Chiang & Ching-Fan Chung & Emily Cremers, 2001. "Promotions and the pattern of grocery shopping time," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(7), pages 801-819.
    16. Ehrenberg, Andrew S. C. & Uncles, Mark D. & Goodhardt, Gerald J., 2004. "Understanding brand performance measures: using Dirichlet benchmarks," Journal of Business Research, Elsevier, vol. 57(12), pages 1307-1325, December.
    17. Michael Platzer & Thomas Reutterer, 2016. "Ticking Away the Moments: Timing Regularity Helps to Better Predict Customer Activity," Marketing Science, INFORMS, vol. 35(5), pages 779-799, September.
    18. Desmond Lam & Richard Mizerski, 2009. "An investigation into gambling purchases using the NBD and NBD–Dirichlet models," Marketing Letters, Springer, vol. 20(3), pages 263-276, September.
    19. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.
    20. Peter S. Fader & Bruce G. S. Hardie & Chun-Yao Huang, 2004. "A Dynamic Changepoint Model for New Product Sales Forecasting," Marketing Science, INFORMS, vol. 23(1), pages 50-65, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:joreco:v:64:y:2022:i:c:s0969698921003751. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.