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Understanding the influence customers have on each other is of critical importance in service research. With consistently growing opportunities to influence other actors through social media, the relationships between a firm and its customers are ever evolving. Customers engage in repeated journeys with the firm and their social networks via online engagement behaviors that go beyond transactions (e.g. e- WOM). Recent research formalizes the value of this influence that a customer exerts on other actors in a network as customer influencer value (CIV); one of the components to assess customer engagement value (CEV). Although customer's influence on actors across service ecosystems is well understood, little is known about how service firms can identify customers with potential high influencer value which is their main challenge to leverage CIV during acquisition efforts. Additionally, thus far, no research has investigated non-customers’ influencer value, especially, to assess whether they will continue to share firm-related posts, and also, whether their posts will continue to have an impact in their social network. This research uses two experimental studies and an online survey. The first study (experiment) aims at identifying customers with potential high degrees of influence by measuring their impact in terms of not only the size of their social network, but also the strength of their online social ties conceptualized based on the close-exchange orientations. The second study (survey) investigates non-customers' likelihood of sharing firm-related posts. Finally, the third study (experiment) measures the impact of non-customers with high influencer value on other actors. Results of the first study show that network size is not a unique identifier of customers with high degrees of influence, and that dependant on the strength of their online social ties, customers with large and even small network sizes will affect other actors’ attitudes and behaviors towards service providers, after accounting for perceived source credibility and motives for generating e-WOM. Our results suggest that service providers should avoid relying solely on large network size to identify customers with potential high influencer value. Customers with small network size and strong ties have a much stronger impact than those with large networks and weak ties. Furthermore, medium ties which have been overlooked in prior research, showed a significant impact on other actors whether accompanied with large or small network size. This study advances empirical research on CIV and contributes to marketing research by providing empirical results that identify customers with high influencer value. The online survey results reveal the likelihood of noncustomers continuing to share firm-related posts and subsequently, the third study (experiment) measures non-customers’ influence value (NCIV) on actors. Finally, this research also provides new insights to win back non-customers with high influencer value.