Bonfire of the Vanity Metrics: Influencer Marketing and Fake Followers
Updated: Apr 10
This was written for CAS 839: Media Analytics Communications in the Michigan State University Strategic Communications MA program.
Influencer marketing (IM) continues to dominate the digital marketing landscape. Leveraging personality and popularity, IM leverages influencers’ social media metrics to endorse, recommend, promote, increase brand awareness and engagement, and sell products and services to niche audiences. IM works best in four categories: compliance; conformity; obedience; and meaningful storytelling (Alhabash, 2020; Alkon, 2018). Regardless of the influencer, the product, or the market, the IM works because influencers create high amounts of trust from followers (Chen, 2020). Brands pay top dollar for influencers (including bloggers, experts, celebrities, and micro-influencers) with wide reach and high follower counts (Driver, 2019). But when influencers purchase likes and followers, they misrepresent themselves in a fraudulent manner as they forego organic analytics for “vanity metrics” (Alscher, 2020, p. 3).
How to Spot a Fake
Many successful and aspiring influencers buy followers for one simple fact: followers create followers (Stewart, 2020). There are many places online to purchase influence (followers, likes, loop giveaways, or even “comment pods”), but savvy users can spot a fake from a mile away through social sleuthing or even through online tools (Driver, 2019, p. 10; Stewart, 2020). There are many tell-tale signs of influencer trickery: sudden spikes in follower counts or engagement; profiles without images and/or few followers, fake user names (especially with long strings of numbers), recently created profiles, increase in non-engaging or redundant comments (especially simple, emoji-based replies); lack of earned media; and illogical follower-to-engagement ratios (10,000 followers with few per-post likes, for example) (Scarratt, 2020; Zote, 2019; Stewart, 2020; Driver, 2019).
Influencer Marketing, Brands, and User Data
When successful, it provides brands with access to user data through cookies from click-throughs and social media data through an application programming interface (API)—software that connects and interacts with external software components) (Dickman, 2019; Freeman, 2019). Armed with user information, brands can target and predict behaviors based on lifestyle, demographics, behavioral intent, and geography. However, there is an ethical barrier to consider because influencers who inflate their metrics, at their core, are misrepresenting themselves. One cannot lie about their assets to qualify for a loan. Similarly, an influencer with fake followers is beginning a contractual relationship based on a fraudulent premise.
If a user grants permission for a website or an app, based on an influencer who (on the surface) seems impressive, then they are the victim of misdirection. To inoculate against potential IM ethical issues, brand leadership should create methodical and quantitative vetting processes—prioritizing engagement over followers, for example—and incorporate regular follow-up monitoring—to ensure the people they choose to represent their brand are trustworthy. Another simple to discourage and dispel fake analytics is to hire influencers based on good, old fashioned SMART goals that are easily monitored and recorded. The Federal Trade Commission compels influencers to reveal brand relationships (Bogliari, 2020). Further regulation is needed to verify the veracity of IM metrics—even a signed statement by influencers declaring truth in representation.
IM is ubiquitous on social media and will continue to act as a marketing catalyst. But as with any industry, accurate representation is crucial to success. Trust is essential to both the influencer-user and influencer-brand relationships. Vanity metrics are flashy but they position influencers unethically and incorrectly based on analytics that are manufactured.
Alhabash, S. (2020). Lecture 11.1: Influencer Marketing. [Video]. Retrieved from the Michigan State University, Digital Media Strategies. Desire 2 Learn: https://d2l.msu.edu/d2l/le/content/1069161/viewContent/9507231/View?ou=1069161
Alkon, J. (2018, June 26). How Logitech uses micro-influencers to promote its products. The Social Shake-Up. https://www.socialshakeupshow.com/logitech-micro-influencers/
Alscher, D. (2020, January 17). Don’t waste your time with vanity metrics: Use these instead. G2 Learning Hub. https://learn.g2.com/vanity-metrics
Bogliari, A. (2020, December 2). Influencer marketing and FTC regulations. Forbes. https://www.forbes.com/sites/forbesagencycouncil/2020/12/02/influencer-marketing-and-ftc-regulations/?sh=1c360fe41566
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Freeman, J. (2019, August 8). What is an API? Application programming interfaces explained. InfoWorld. https://www.infoworld.com/article/3269878/what-is-an-api-application-programming-interfaces-explained.html
Stewart, A. (2020, July 8). Fake followers and buying engagement: Influencer trickery may be coming to an end. The National News. https://www.thenationalnews.com/lifestyle/fake-followers-and-buying-engagement-influencer-trickery-may-be-coming-to-an-end-1.1046016
Zote, Jacqueline. (2019, July 23). What are fake influencers and how can you spot them? Sprout Social. https://sproutsocial.com/insights/fake-influencers/