See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/319796276 Influencer Engagement Strategies – Frameworks for Brand Managers Conference Paper · January 2013 CITATIONS READS 0 441 1 author: Arpan Kumar Kar Indian Institute of Technology Delhi 135 PUBLICATIONS 825 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: Electoral preferences and Social media View project Open Publishing View project All content following this page was uploaded by Arpan Kumar Kar on 16 September 2017. The user has requested enhancement of the downloaded file. Kar, A.K. and Chakraborty A. (2017). Influencer Engagement Strategies – Frameworks for Brand Managers. Business Frontiers, Vol. 9. PP. 1-3. Influencer Engagement Strategies – Frameworks for Brand Managers Kar, A.K.. Business Fundas, http://business-fundas.com Convent Road, Kolkata, India editor.blogging@gmail.com Chakraborty, A Tech Talk, http://tech-talk.org Khidderpore, Kolkata, India editor.webposts@gmail.com Abstract— Influencers have grown from a non-traditional method of brand promotion to one of the more effective strategies in all of marketing. Brands must build a connection with their audience in order to be successful. This involves gaining their attention, building trust, and making sure the entire effort doesn’t sound too much like a pitch. Brand influencers bring a sense of authority and credibility to these efforts. They can incentivize viewers to check out content they may have otherwise passed on, and even help brands expand their audience in the long-term. Here are a few ways brands are activating influencers in 2017. around these influencers as an extension of strategies of native advertising and subliminal advertising. Keywords—Digital Marketing, Social Media Marketing, Marketing Communications, Web 3.0, Influencer Marketing. I. INTRODUCTION Influencers have grown from a non-traditional method of brand promotion in this digital era to one of the more effective strategies in all of marketing. Brands must build a connection with their audience in order to be successful. This involves strategies for gaining their attention, building trust with stakeholders, and making sure the entire effort doesn’t sound too much like a marketing or sales pitch. A lot of subliminal advertising strategies are implemented through influencer engagement. Brand influencers bring a sense of authority and credibility to these efforts. They can incentivize viewers to check out content they may have otherwise passed on, and even help brands expand their audience in the longterm (Brown & Hayes, 2008). There are many obstacles standing in the way of that influencer engagement, the least of which (but no less challenging) being continuity. Experienced marketing managers and product developers will learn to plan around these roadblocks. Here are a few ways brands are activating influencers in 2017. II. AN OVERVIEW OF CHALLENGES In this era of digitization, influencer marketing (also influence marketing) is a form of marketing in which focus is placed on influential people rather than the target market as a whole (Kar, 2014a; Kar, 2014b). The strategy focuses on identifying the individuals that have influence over potential buyers, decision makers, consumers and orients marketing activities Figure 1: Influencer Marketing Process Funnel Brand Influencers Can Highlight Areas of Expertise People like getting their information from those who are in the know, and brand influencers bring the necessary authority to boost a content’s reach. Brands want to be viewed as trustworthy, and this means enlisting the help of people who have plenty of experience in the areas they’re trying to focus on (Erdoğmuş & Cicek, 2012). Expert insight can also help a brand come across as more fact-focused and informative than salesy or pitch-based. This means that the communicated message needs to be in media as a form of native advertising (Ferguson, 2008). One of the best ways to use a brand is by appealing to the individual directly. A common practice in content marketing, brand marketing also benefits from a viewerfocused model. The easiest way to implement this is to allow for interaction between creators and their audience. Using Influencers to Encourage Interaction One of the most difficult things for many brands is getting a two-way conversation going. Interacting with viewers and subscribers is conducive to long-term engagement. People will stay around when they’re part of the discussion (Kim & Ko, 2012). Brand influencers can incentivize even the most reserved individual to comment on and interact and share their opinions on a piece of content or even the brand as a whole. Influencers help brands acquire feedback this way, making it easier for them to adapt and grow. Sometimes a brand may grow as a direct result of the feedback they receive. When there is a disconnect between a brand and their audience, influencers can function as a great way to bridge the gap through social interactions which can be actively and objectively captured and measured through emerging technologies like social CRMs (Kar, 2015). Sometimes a familiar face with a good standing is enough to put any brand on the right track. Selection of influencers Selection of influencers fall under the classic vendor selection problem (Kar et al., 2011). Literature indicates that the vendor selection problem is a multi-criteria decision making problem which has both qualitative and quantitative criteria for assessment (Pani & Kar, 2011; Kar, 2013a; Kar, 2013b). Similarly, identifying influencers is a tough job amidst all the spam created in social media where individuals strive to showcase popularity and hence demonstrate influence for personal and commercial reasons. Digital marketing space is hence filled with spam profiles which is difficult to segregate and requires machine learning algorithms and advanced analytics approaches (Chakraborty & Kar, 2016; Chakraborty & Kar, 2017). Focusing on Specific Issues and Areas Being a niche brand can be extremely difficult, as these lesser-known areas are usually harder to make an impact in. Though there may be less competition, those who specialize in these areas usually have high expectations. For brands focusing on very specific issues and ideas with their efforts, sometimes getting the right influencer can truly put things in motion (Subramani & Rajagopalan, 2003). A good example of this is Vanessa Selbst, a high-ranking poker player who focuses her efforts on various equal rights issues. Selbst is the top women’s poker player on the planet with earnings of over $11.6 million. As a Texas Hold’em standout, Selbst has been an advocate for women in sport for many years. Her high profile has been an asset to influence young women to start playing poker and other sports. Brands are using influencers when narrowing their efforts, allowing them to gain the proper credibility when entering new territory. The functional blocks of social media facilitate in the decision making process in this context (Mangold & Faulds, 2009). When it comes to gaining a good reputation quickly, being in good company is important. Brand influencers can incentivize even the most reserved individual to comment on and interact and share their opinions on a piece of content or even the brand as a whole. Influencers help brands acquire feedback this way, making it easier for them to adapt and grow. III. CONCLUSION The digitization of products and processes have significant impact on the outcome of any industry operating in Industry 4.0 in terms of massive improvements of expectations from all stakeholders. With the emergence of digital marketing using platforms of web 3.0, this is further going to take the product commercialization to a new level with the influx of sensor driven practices and big data analytics showing the way (Chauhan et al., 2016). Digital businesses like e-commerce portals would have to take in the perspective of the user groups and multiple stake-holders to remain competitive (Kalelkar et al., 2014). We feel that the conceptual model of academic research would benefit the practice if utilized significantly. It is imperative for future research to address these concerns of current limitations of business models by the digitization of both products and processes. REFERENCES Chauhan, S., Agarwal, N., Kar, A. K., & (2016). Addressing big data challenges in smart cities: a systematic literature review. info, 18(4), 73-90. Brown, D., & Hayes, N. (2008). Influencer marketing: Who really influences your customers?. Routledge. Ferguson, R. (2008). Word of mouth and viral marketing: taking the temperature of the hottest trends in marketing. Journal of consumer marketing, 25(3), 179-182. Subramani, M. R., & Rajagopalan, B. (2003). Knowledge-sharing and influence in online social networks via viral marketing. Communications of the ACM, 46(12), 300-307. Kar, A. K. (2014a). A group decision support system for selecting an open source tool for social media integration. In Emerging Trends in Computing and Communication (pp. 407-413). Springer, New Delhi. Kar, A. K. (2014b). A Decision support system for website selection for internet based advertising and promotions. In Emerging Trends in Computing and Communication (pp. 453-457). Springer, New Delhi. Kar, A. K. (2015). Integrating websites with social media–An approach for group decision support. Journal of Decision Systems, 24(3), 339-353. Kar, A. K., Pani, A. K., Mangaraj, B. K., & De Supriya, K. (2011). A soft classification model for vendor selection. International Journal of Information and Education Technology, 1(4), 268. Kar, A. K. (2013a). Using artificial neural networks and analytic hierarchy process for the supplier selection problem. In Signal Processing, Computing and Control (ISPCC), 2013 IEEE International Conference on (pp. 1-6). IEEE. Kar, A. K. (2013b). An approach for prioritizing supplier selection criteria through consensus building using Analytic Hierarchy Process and Fuzzy set theory. In Signal Processing, Computing and Control (ISPCC), 2013 IEEE International Conference on (pp. 1-6). IEEE. Chakraborty, A., & Kar, A. K. (2017). Swarm intelligence: A review of algorithms. In Nature-Inspired Computing and Optimization (pp. 475-494). Springer International Publishing. Chakraborty, A., & Kar, A. K. (2016). A Review of Bio-Inspired Computing Methods and Potential Applications. In Proceedings of the International Conference on Signal, Networks, Computing, and Systems (pp. 155-161). Springer India. Pani, A. K., & Kar, A. K. (2011, January). A study to compare relative importance of criteria for supplier evaluation in e-procurement. In System Sciences (HICSS), 2011 44th Hawaii International Conference on (pp. 1-8). IEEE. Kalelkar, G. R., Kumbhare, G., Mehta, V., & Kar, A. K. (2014, February). Evaluating E-Commerce Portals from the Perspective of the End User-A Group Decision Support Approach. In SIRS (pp. 107-117). Kim, A. J., & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research, 65(10), 1480-1486. Erdoğmuş, İ. E., & Cicek, M. (2012). The impact of social media marketing on brand loyalty. ProcediaSocial and Behavioral Sciences, 58, 1353-1360. Mangold, W. G., & Faulds, D. J. (2009). Social media: The new hybrid element of the promotion mix. Business horizons, 52(4), 357-365. View publication stats