Phd Canditate :

E-mail :

Supervisor :

Anastasia Griva


Assoc. Professor K. Pramatari

PhD Thesis Abstract

The abundance of data reflecting customer behavior and the continuous changes in modern shopper behavior revives segmentation literature in contemporary retail. Motivated by this fact, this research proposes a visit segmentation approach that reveals the shopping intentions/ missions that induced consumers’ visits. By examining shopper behavioral data, in visit level we identify the underlying needs that boosted a customer to visit a store e.g. to procure materials to renovate the bathroom, to buy professional clothes, to prepare a dinner etc.. We applied and evaluated the proposed approach in three heterogeneous retailers with different sale channels and product types. During the application of the approach, we identified several shopper, retailer and data-related factors that affect the segmentation. Thus, this research also provides a set of factors that managers in the retail industry, as well as marketeers and data scientists should consider when designing segmentation systems and approaches. These factors not only affect the segmentation process, but also the shopper marketing decisions that our approach enables. Apart from evaluating the proposed business analytics approach by applying it to the different retail cases, we also evaluate the impact of our approach. For that reason, we conducted semi-structured focus groups to discuss with actual shoppers (shopping at the store the data derived) and ask for their view on the resulting visit segments/shopping missions. Additionally, we designed an in-store field study to evaluate the resulting data-driven shopping missions and asses their validity in the context of a specific in-store promotion using a mobile app. We demonstrate that the shopping mission-related disseminated coupons achieve higher redemption rate and are claimed by shoppers in less time than the non-related coupons. Closing, we further present data-driven innovations in shopper marketing that the resulting visit segments could support, ranging from marketing campaigns per visit segment and redesign of a store’s layout to cross-selling strategies and product recommendations.