The aim of this study was to determine consumer segments based on the acceptance of shoppable ads from fashion brands on online social media platforms. To achieve this objective, we used the technology acceptance model (TAM) to offer a vision of the perceptions of the shoppable ads, attitudes and behaviors of social network users, using social media marketing activities as a background. Second, we searched for fashion social buyer segments using finite mixture partial least squares (FIMIX-PLS). Third, we sought to characterize these consumer segments. A sample of 486 users of social networks who accessed through mobile devices was obtained. The inclusion of social media marketing variables as antecedents of acceptance allowed us, to a large extent, to understand the intention to buy clothing by these social media users. The a posteriori segmentation technique helps to identify different types of users who use shoppable ads and their relationship with age and concerns about privacy, trust and purchases made on the Internet. The results show that, based on the explained variance and model fit, the proposed variables allow us to explain acceptance, with two groups of consumers within the sample being found.