Does Online Information Drive Offline Revenues? Only for Specific Products and Consumer Segments!

By Koen Pauwels, Peter S. H. Leeflang, Marije L. Teerling, K. Huizingh. 2011

233 citations recorded by the source corpus.

While many offline retailers have developed informational websites that offer information on products and prices, the key question for such informational websites is whether they can increase revenues via web-to-store shopping. The current paper draws on the information search literature to specify and test hypotheses regarding the offline revenue impact of adding an informational website. Explicitly considering marketing efforts, a latent class model distinguishes consumer segments with different short-term revenue effects, while a Vector Autoregressive model on these segments reveals different long-term marketing response. We find that the offline revenue impact of the informational website critically depends on the product category and customer segment. The lower online search costs are especially beneficial for sensory products and for customers distant from the store. Moreover, offline revenues increase most for customers with high web visit frequency. We find that customers in some segments buy more and more expensive products, suggesting that online search and offline purchases are complements. In contrast, customers in a particular segment reduce their shopping trips, suggesting their online activities partially substitute for experiential shopping in the physical store. Hence, offline retailers should use specific online activities to target specific product categories and customer segments.

Subfields: Marketing

View Paper: https://www.semanticscholar.org/paper/cf240f5c270271181b755e7f5b56568b5697287e

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Citations in the corpus

The digitalization of retailing: an exploratory framework (2016, background): “…e-commerce and includes the transformation of physical products into digital services, consumer recommendations in social media, and the incorporation of digital devices into the purchasing process—such as online information searches leading to offline purchases (see, e.g., Pauwels et al ., 2011).”
Buying Groceries in Brick and Click Stores: Category Allocation Decisions and the Moderating Effect of Online Buying Experience (2015, background): “Not being able to see or touch products can complicate the evaluation process and lead to greater uncertainty and a higher perceived risk of online purchases (Laroche et al. 2005; Pauwels et al. 2011; Weathers, Sharma, and Wood 2007).”
Driving Online and Offline Sales: The Cross-Channel Effects of Traditional, Online Display, and Paid Search Advertising (2013, methodology): “Researchers have only begun to investigate the crosschannel effects of online activities on offline sales (Chan, Wu, and Xie 2011; Danaher and Dagger 2013; Pauwels et al. 2011; Van Nierop et al. 2011) as well as the impact of offline activities on online sales and consideration (Naik and Peters 2009”
Gameful Experience in Gamification: Construction and Validation of a Gameful Experience Scale [GAMEX] (2018, background): “…of specific gaming experiences, that is, immersion (Cheng, She, and Annetta 2015; Qin, Rau, and Salvendy 2009), flow (Fu, Su, and Yu 2009; Pauwels et al. 2011; Rheinberg, Vollmeyer, and Engeser 2003), and presence or telepresence (Lombard, Weinstein, and Ditton 2011; Moreno and Mayer…”
What factors determine e-satisfaction and consumer spending in e-commerce retailing? (2017, background): “MARK and service, up-to-date technology, and poor design of website pages (Pauwels et al., 2011; Bamfield, 2013).”
eWOM as Source of Influence: The Impact of Participation in eWOM and Perceived Source Trustworthiness on Decision Making (2014, background): “There is a huge amount of online information about any product that can be consulted with relatively minimal expenditure of both time and effort (Pauwels et al. 2011).”