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    Sosyal ağlarda influencer pazarlama: Instagram'da tüketici segmentlerinin belirlenmesi ve erkin influencer tespiti
    (İstanbul Bilgi Üniversitesi, 2021) Gevrek, Elif; Durmuş, Beril
    ABSTRACT: Marketing refers to the activity of creating value to consumers, to attract their attention and manage profitable relationships with them (Kotler et al., 2017). In today’s world, influencer marketing is an important strategy to catch consumer attention. One of the most preferred methods of brands to reach consumers who spend a lot of time on digital platforms and social networks, is through an influencer. Influencer marketing—essentially a form of word of mouth marketing—is widely used. Due to the global spread of the internet, word of mouth marketing is coined as electronic word of mouth marketing which enables marketing messages to circulate among audiences. Social media is a very strong tool for many brands. Brands which cooperate with influencers with thousands or even millions of followers, can easily reach their own target audiences through those influencers. Although the follower number of an influencer is crucial somewhere along, the attributions of the followers get ahead of its quantity. Not only a large following of the influencer but also the features and interests of followers is of vital importance. Influencers based on their spectrum are classified into three groups as micro, macro and mega influencers. All the niche-focused micro influencers with a decent following, the macro influencers with large follower counts and the mega influencers with millions of followers are the most talked about personalities in the marketing world. Basically influencers, in their own way, connect the brand’s message with its target consumers. Influencers can also be referred to as “bloggers” but in this research, the term “influencer” is preferred because of its deep penetration into the academic literature and our daily lives. What is important for a brand is to be able to collaborate with the right influencers, enabling them to represent the brand name in the best way possible. Working with different influencers that appeal to different audiences is a more profitable and effective strategy than working with separate influencers adressing the same audience. The right influencer should convey the right message to the right audience. Having done the segmentation of the users of a brand on social networks, it is vital for the brand to conceive the dynamics and the related behaviours of each segment. Social data displays those behaviours and clusters in a clear way to us. Discovering those clusters is very important because obtaining those clusters with the right people in them is a life-sustaining value for a brand’s perspective. This way, it is possible to generate unique messages to each cluster of followers and to detect accurate influencers who can convey those messages. The goal of this study is, by following the footprints of consumers in the social data and using the network mapping technique, to be able to analyse deeply the segments that people as social beings belong to, to acquire insights about their changing behaviour, developing strategies and detecting efficient influencers for each segment. This research not only aims to analyse every cluster on social network along with its dynamics but also to specify the influencers who have the power to transform those dynamics, and thus to deal with the subject of influencer marketing in a deep and conmprehensive way. This research is realised by using the software NSATM (Network Structure Analysis) which is developed by Deeper Data Technologies—a company working in the area of data-based behavioral marketing. This software can analyse follower clusters of social networks and respond to many questions that are crucial for a brand. The case study of this research project is the mother and child sector on Instagram. Examining this particular category, not only the issue of influencer marketing on social networks has been analyzed, but also consumer segments and efficient influencers have been identified. What makes this project unique and unlike other research projects is the analysis and visualization of the social data with the use of the network mapping technique. In this sense, this thesis is offered in the hope of making a contribution to the current literature, and shedding light on future research in this growing field.