Personal brand value extraction method to identify micro-influencer for effective digital marketing

Abstract Along with the growth of social networks, social marketing, and influencer marketing, the analysis of influencers, especially the analysis of micro-influencers on social networks, is an interesting topic. Various approaches have been proposed for this problem, but there is still a research gap that no effort meets these requirements to determine micro-influencers. This study introduces a novel methodology for identifying influencers within social networks, utilizing three distinct metrics. These metrics include the amplification factor , which evaluates the spread of information, the passion point , measuring preferences of users for a brand or its offerings, and the content creation score , estimating proficiency of a user in generating social media content. The research compares its approach with several recent methods, establishing a baseline for assessment. Additionally, the proposed methodology is implemented to construct a management system for affiliate marketing campaigns. Beyond determining potential influencers, this system effectively oversees influencers’ impact on react-to-purchase conversion rates, contributing to a favorable return on investment in marketing campaigns employing the identified influencers.