Digital influencers have become highly relevant to consumers, occupying a space between peers and traditional celebrities by sharing expertise as well as aspirational, yet often attainable, lifestyles. As a result, brands have increasingly turned to influencer marketing as a way to target specialized audiences and co-opt the influencer-consumer relationship. While this strategy has proven largely successful, it has also led to concern about transparency and trust on both sides of the fence. For brands and consumers alike, ensuring that the follower count of a particular influencer is real and not artificially inflated is a pertinent issue.
From Twitter’s latest policy aiming to combat spam to Unilever’s CMO announcing that “the company is pushing for greater transparency in the influencer marketing space,” it’s clear that the topic of fraud is now being addressed with greater frequency.
And there is incentive to figure it out, as influencer marketing continues to grow in value for both marketers and consumer audiences. In fact, 79 percent of influencers are planning to create more branded posts than they currently do this year, and influencer marketing ad spend is expected to reach between $5 billion and $10 billion by 2022. So, what can brands do to take advantage of this lucrative opportunity without the risk of inaccurate targeting and a loss of authenticity in their approach? Fortunately, technology is expected to play a larger role in fighting fraud with a number of growing solutions available to help combat prevalent issues such as fake followers and spam bots.
In an era where trust is declining for companies that don’t prioritize consumer preferences, leveraging the right micro-influencers is an opportunity for brands to better relate to customers through a strategy steeped in authenticity. But, in order to ensure true authenticity from an influencer, brands also must be more mindful of how fraud in the influencer space can create inflated metrics, which ultimately impacts the effectiveness of a brand’s campaign. That said, it’s now more important than ever to ensure your marketing activities, including your influencer strategy, are not only compliant, but also have accurate information to help your brand make the most of its marketing spend. To learn how to identify fraudulent influencers as well as understand how the right technology can help your brand do so, read on below.
First, in order to combat influencer marketing fraud, it’s important to understand what it is. While this type of marketing is still deemed quite effective for brands, there have been growing issues with influencers boosting their status using fake followings and engagement. Don’t let fraud get in the way of executing effective influencer campaigns! Instead, focus on perfecting the ability to identify when fraud is occurring so your company can curb the behavior and ensure consistent understanding of influencer campaign performance. Here are two of the most common types of fraud:
- Follower Fraud: When the following of an influencer is heavily boosted by spam accounts or bots to feign an active audience and grab the attention of brands.
- Engagement Fraud: When the majority of likes or comments on an influencer’s post are posted by fake accounts or bots to feign a better engagement rate on their posts.
While strict influencer vetting is critical for any company that hopes to create an effective campaign, human identification of fraudulence can only go so far. Of course, brand vetting is still crucial in identifying whether an influencer fits with the brand voice and experience, but adequate technology is imperative to obtain the full picture of an Instagram creator.
We understand the challenges many companies face with influencer campaign efficiency and impact, and that’s why we have emphasized combating fraud in our own Creator Platform.
With the latest proprietary technology, we investigated a sample of almost 4,000 Instagram influencers with at least 5,000 followers and found that almost 10 percent engaged in fraudulent behavior through buying followers or engagements.
That’s why we now have a machine-learning algorithm that assesses a statistically significant sample of an influencer’s followers, as well as accounts that like or comment on their posts in order to determine if an account is a real person or a bot. To do this, we look at a variety of different attributes, including:
- An unrealistic ratio of followers to following (we have a benchmark of what the ratio should be based on years of data)
- A spike in followers from developing countries
- An unusual increase in number of followers of a period of time
- Any unrealistic engagement activity
Using our technology and the above attributes, our platform is then able to automatically analyze and flag any influencers as being high, medium, or low risk of having purchased followers or engagements. This helps companies easily ensure their campaigns are being executed by the creators who best fit a brand’s goals and also provides cleaner, more accurate information on influencer campaigns for more efficient marketing spend.
No matter the stage of the influencer marketing journey your company is in, it’s critical to have the right procedures and technologies in place to ensure your campaigns reach their full potential. To learn more about how Olapic can help streamline your brand’s influencer management strategy and combat creator fraud, request a demo here.