The influencer marketing industry is projected to be worth $5 to $10 billion by 2020, but research shows up to 24 percent of influencers have falsely manipulated their engagement numbers. She worked with 22 different brands in 2018 and charged $1,000 per post. Those brands didn’t realize that 96 percent of Jess’s engagement is fake, the result of a bot farm she allegedly paid for engagement: $2 for every 1,000 likes, comments or shares. Fake followers are another enduring issue on social media platforms, but they’re easier to track and identify -- simply compare an account’s number of followers to its average engagement rate (number of likes, comments and/or shares per post). The tool uses machine learning to cross-reference those profiles with hundreds of thousands of influencer’ accounts, flag suspicious activity and generate an “engagement graph” that compares the influencer’s engagement over time with an organic engagement curve. We've seen the influencer marketing industry develop in shifts over the past couple of years. We’re not a tech business, but we worked with developers to build a piece of software to bring this tool to life -- coming up with an index of what real engagement looks like, surveying a decent sample size and looking at about eight posts from each account to get an indicative benchmark of their engagement curve and velocity. There was a real variety: Some manipulated just slightly on their sponsored posts, while in extreme cases, engagement was manipulated up to about 95 percent. For example, let’s say that in an extreme case, a talent had 10,000 followers and she generated 500 likes, comments and shares on a post -- we could indicate based on growth patterns that 95 percent of that was manipulated and only 5 percent was real engagement. One important question right now in the influencer marketing industry is: How do we protect ourselves?
The influencer marketing industry is projected to be worth $5 to $10 billion by 2020, but research shows up to 24 percent of influencers have falsely manipulated their engagement numbers.
Jess (not her real name) is a U.K.-based fashion influencer with 230,000 Instagram followers. She worked with 22 different brands in 2018 and charged $1,000 per post.
Those brands didn’t realize that 96 percent of Jess’s engagement is fake, the result of a bot farm she allegedly paid for engagement: $2 for every 1,000 likes, comments or shares. That means that each company Jess worked with likely wasted up to $960.
It’s called “influencer fraud,” a practice spawned after the digitalization of influencer marketing — the latter of which has, in one iteration or another, been around for hundreds of years. Prominent online personalities purchase fake engagement via bots — pieces of software designed to automatically like, comment and share social media posts. The other route is to join a community of real users that allows people to “trade” engagement back and forth (e.g., commenting on or liking 250 posts from others in the community to receive 250 comments or likes on your own posts).
Fake followers are another enduring issue on social media platforms, but they’re easier to track and identify — simply compare an account’s number of followers to its average engagement rate (number of likes, comments and/or shares per post). Fraudulent engagement, on the other hand, can cost companies millions — especially in a market projected to be worth $5 to $10 billion by 2020. Until now, there was no real way to track it.
Enter Like-Wise. Launched in the U.S. in January 2019, it’s billed as the first tool using AI to comb through influencers’ profiles to detect discrepancies in engagement. It’s a useful way for brands to verify they’re paying for real eyes on their products when they enter into an ad partnership with an influencer, and Like-Wise now counts Amazon, FIFA, Tik Tok, Disney, Nokia, Dreamworks, NBC Universal, Superdry, Häagen-Dazs and more among its users.
Like-Wise collected data from bot farms to build a database of tens of millions of profiles that generate fake engagement on influencers’ pages. The tool uses machine learning to cross-reference those profiles with hundreds of thousands of influencer’ accounts, flag suspicious activity and generate an “engagement graph” that compares the influencer’s engagement over time with an organic engagement curve.
“Upon launching the tool, we had over a thousand inquiries in the space of three days,” said Oliver Yonchev, managing director of the U.S. arm of Social Chain, the social media marketing agency that developed Like-Wise. “It was clear to us that it was a systemic issue and people really cared about it.”
Social Chain acts as a middleman in booking about a thousand influencers per month to work with its clients and originally launched Like-Wise for in-house use. Now, they’ll use the tool as an “insurance policy” of sorts for their clients, usually charging an influencer 5 percent of the influencer’s own fee to run the audit (akin to paying for your own background check). The company will also conduct an influencer audit for anyone who asks, client or not — cost ranges from $7,250 for up to 50 influencers and $35,000 for up to 400. Social Chain said after the launch of Like-Wise, they expect influencer marketing-related activity will account for 40 percent of their business by year-end, but the company declined to share specifics on revenue, citing an…
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