Abstract

The aim of this research is to find a segment of consumers of fashion products based on their personal visions of personalization of shoppable ads on mobile social media. To meet this objective, three operational objectives are defined. First, a theoretical model is evaluated based on the stimulus-organism-response framework (S-O-R). This examines, with a PLS-SEM approach, how the stimulation of personalization will affect consumers' internal cognitive state (perceived usefulness) and consequently generates a behavioral response (intention to buy). Second, we look for fashion consumer segments based on their perception of personalization through prediction-oriented segmentation (PLS-POS). Third, the segments are explained based on three constructs that were considered important in fashion consumption through mobile social networks: purchase intention, concern for privacy, and perception of trend. The inclusion of personalization and the perception of usefulness of advertisements can greatly help the intention to purchase clothing to be understood. The application of a posterior segmentation helps to better understand the different types of users exposed to shoppable ads on mobile social networks and their relationship with the purchase intention, concern for privacy and trend. While the measures and scales were tested in a context of mobile clothing trade, the methodology can be applied to other types of products or services.