Ranking of advertising goals on social network sites by Pythagorean fuzzy hierarchical decision making: Facebook

Abstract

The rapid growth of social networking sites (SNSs), known as web-based services, has become a natural digital phenomenon, reinforcing e-commerce concepts such as business-to-consumer (B2C) and consumer-to-consumer (C2C), known as social commerce. One platform that provides end-to-end connections, from increasing brand awareness to creating new opportunities in the contemporary marketing approach, is Facebook, which reaches a broad audience of advertisers with the advantage of many users. Facebook has updated its ad targets in recent years. Choosing the right advertising target will directly affect company and campaign performance. Considering this problem structure, it is compatible with fuzzy set theory since it contains conflicting criteria and high complexity in an environment of uncertainty. As far as it is known from the literature, although there are many academic studies on Facebook ad analysis, there is no study investigating advertising targeting with fuzzy set theory. Therefore, in the decision model developed for Facebook advertising targeting, a fuzzy decision model is proposed for targeting by the campaign structure. The first stage of the model includes the combined use of AHP-TOPSIS methods by evaluating performance criteria and presenting advertising targets in social media campaigns with Pythagorean fuzzy sets. As a result, it has been reached that the awareness-raising strategy for local or global users should include campaign activities that will increase brand awareness.