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The Value of Descriptive Analytics: Evidence from Online Retailers

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  • Ron Berman

    (Marketing, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Ayelet Israeli

    (Marketing Unit, Harvard Business School, Boston, Massachusetts 02163)

Abstract

Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we find an increase of 4%–10% in average weekly revenues postadoption. We demonstrate that only retailers that adopt and use the dashboard reap these benefits. The increase in revenue is not explained by price changes or advertising optimization. Instead, it is consistent with the addition of customer relationship management, personalization, and prospecting technologies to retailer websites. The adoption and usage of descriptive analytics also increases the diversity of products sold, the number of transactions, the numbers of website visitors and unique customers, and the revenue from repeat customers. In contrast, there is no change in basket size. These findings are consistent with a complementary effect of descriptive analytics that serve as a monitoring device that helps retailers control additional martech tools and amplify their value. Without using the descriptive dashboard, retailers are unable to reap the benefits associated with these technologies.

Suggested Citation

  • Ron Berman & Ayelet Israeli, 2022. "The Value of Descriptive Analytics: Evidence from Online Retailers," Marketing Science, INFORMS, vol. 41(6), pages 1074-1096, November.
    • Handle: RePEc:inm:ormksc:v:41:y:2022:i:6:p:1074-1096
    DOI: 10.1287/mksc.2022.1352
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    References listed on IDEAS

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    1. Hannes Datta & George Knox & Bart J. Bronnenberg, 2018. "Changing Their Tune: How Consumers’ Adoption of Online Streaming Affects Music Consumption and Discovery," Marketing Science, INFORMS, vol. 37(1), pages 5-21, January.
    2. Dursun Delen & Sudha Ram, 2018. "Research challenges and opportunities in business analytics," Journal of Business Analytics, Taylor & Francis Journals, vol. 1(1), pages 2-12, January.
    3. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2021. "Synthetic Difference-in-Differences," American Economic Review, American Economic Association, vol. 111(12), pages 4088-4118, December.
    4. Puneet Manchanda & Grant Packard & Adithya Pattabhiramaiah, 2015. "Social Dollars: The Economic Impact of Customer Participation in a Firm-Sponsored Online Customer Community," Marketing Science, INFORMS, vol. 34(3), pages 367-387, May.
    5. Germann, Frank & Lilien, Gary L. & Fiedler, Lars & Kraus, Matthias, 2014. "Do Retailers Benefit from Deploying Customer Analytics?," Journal of Retailing, Elsevier, vol. 90(4), pages 587-593.
    6. Wooldridge, Jeffrey M., 2019. "Correlated random effects models with unbalanced panels," Journal of Econometrics, Elsevier, vol. 211(1), pages 137-150.
    7. Eli Ben‐Michael & Avi Feller & Jesse Rothstein, 2022. "Synthetic controls with staggered adoption," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 351-381, April.
    8. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    9. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    10. Alberto Abadie, 2021. "Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects," Journal of Economic Literature, American Economic Association, vol. 59(2), pages 391-425, June.
    11. Riju Joshi & Jeffrey M. Wooldridge, 2019. "Correlated Random Effects Models with Endogenous Explanatory Variables and Unbalanced Panels," Annals of Economics and Statistics, GENES, issue 134, pages 243-268.
    12. Andrew Goodman-Bacon, 2018. "Difference-in-Differences with Variation in Treatment Timing," NBER Working Papers 25018, National Bureau of Economic Research, Inc.
    13. Blum, Bernardo S. & Goldfarb, Avi, 2006. "Does the internet defy the law of gravity?," Journal of International Economics, Elsevier, vol. 70(2), pages 384-405, December.
    14. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    15. Bradlow, Eric T. & Gangwar, Manish & Kopalle, Praveen & Voleti, Sudhir, 2017. "The Role of Big Data and Predictive Analytics in Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 79-95.
    16. Han, Chirok, 2016. "Efficiency comparison of random effects two stage least squares estimators," Economics Letters, Elsevier, vol. 148(C), pages 59-62.
    17. Lismont, Jasmien & Vanthienen, Jan & Baesens, Bart & Lemahieu, Wilfried, 2017. "Defining analytics maturity indicators: A survey approach," International Journal of Information Management, Elsevier, vol. 37(3), pages 114-124.
    18. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    19. Jeffrey M. Wooldridge, 2005. "Fixed-Effects and Related Estimators for Correlated Random-Coefficient and Treatment-Effect Panel Data Models," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 385-390, May.
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