소매점 쇼핑 중 모바일앱 이용의 옴니채널적 가치: 커피소매점 내에서의 전용 모바일앱 이용을 중심으로 = Omni-channel Value of Mobile Application Usage in Off-line Retail Store: Focusing on the Use of Brand App of a Coffee Retailer

다국어 초록 (Multilingual Abstract)

Purpose: In this study, using a marketing research company’s consumer panel data of consumer’s mobileapplications (apps) usage, off-line location and payment, we analyzed the impact of consumer’s in-store mobileapplication (app) usage time on the store’s sales (i.e., consumer’s payment amounts). While lots of previousstudies have analyzed the effects of online and offline channel operation at the retailer level rather than theconsumer level and with a cross-channel perspective rather than an omni-channel perspective, we analyzed theeffects of online and offline channel operation at the consumer level with an omni-channel perspective.
Research design, data, and methodology: We choose one of the biggest coffee retailer who has successivelyintroduced its own mobile app in its retail operation. In any off-line store of the coffee retailer, consumers can usethe mobile app for various omni-channel shopping purposes including in-app information search, in-app order,and in-app payment. Consumers can make an in-app order while he/she is in the off-line store or just beforehe/she visits the off-line store, and can pickup his/her order at the off-line store’s counter including drive-through.
By combining three kinds of panel data (app usage, off-line location, and payment), we traced 227 consumerpanels during the two years of 2022 and 2023 to figure out how much time they used the app in the off-line storeand how much they paid at the coffee retailer. Then we analyzed the impact of customer’s omni-channel shoppingbehavior (which was manipulated as the time spent by panel consumers using the mobile app while staying in theoff-line store) on the payment amounts. To analyze the causal relationship between the in-store app usage timeand the payment amounts, we applied a latent class regression analysis to reflect the consumer heterogeneity inthe omni-channel shopping behavior.
Results: Consumers can be divided into three latent classes (or clusters) according to the level of omni-channel shopping behavior : traditional off-line channel oriented consumers (LC1: latent class 1), on-line channel orientedconsumers (LC2: latent class 2), and customers using both on-line and off-line channels together (LC3: latentclass 3). While the percentage of consumers with omni-channel shopping behaviors is not high, the amount spentof these omni-channel consumers is higher than the traditional off-line channel oriented consumers. Our resultsalso show that in-store app usage time had a statistically significant positive (+) effect on the payment amounts inLC2 and LC3.
Conclusions: The implications of this study can be summarized as follows. First, this study confirmed the valueof omni-channel shopping at the consumer level by empirically showing the significant effect of consumers’in-store app usage time on the payment amounts. Second, in order to reflect the consumer heterogeneity in theomni-channel shopping behavior, we conducted a study that applied latent class regression analysis to classifyconsumer classes (or clusters) according to the levels of omni-channel shopping behavior and integrated causalanalysis with the latent classes (or clusters). Finally, the analysis results of this study can also be meaningfullyused to establish retail strategies to increase omni-channel shopping value by actively utilizing mobile apps whileconsumers stay in off-line retail stores.