Following recent research by Buzzoole which revealed that 15 to 20% of Instagram accounts use fraudulent techniques, the software platform has developed proprietary technology that can identify fake accounts, fake followers and fake engagements or interactions.
Based on opted-in first-party data collected from Instagram Business Accounts supplied by actual influencers and creators on Buzzoole’s platform, the technology will deliver to brands influencers who can guarantee real audiences, genuine engagements and robust results.
When influencers sign up to the Buzzoole platform they provide access to their social media accounts, blogs, and data such as Google analytics, Instagram and Facebook insights. Using machine learning algorithms, Buzzoole technology processes this data and allows brands to see a more complete picture of the influencers being used and the results of their campaigns, making it much harder for them to use fraudulent techniques and giving clients more confidence to invest.
The technology uses a range of in-depth methodologies including analysis of the reach-to-followers ratio (a main indicator of authenticity) and engagement-to-reach (if interactions are much higher than the reach, automated engagement may be at play), plus scrutiny of follower growth and daily active followers.
Ian Samuel, CCO at Buzzoole, said: "Since its inception, Buzzoole has been at the forefront of the battle against influencer fraud. The key in winning this battle is first party, opted in data from platforms like Instagram. If you are using algorithms based on poor or erroneous data then you are going to get the wrong recommendations and the wrong outcomes.
“Plugging into this data means we can perfectly match influencers to briefs, deliver rich analytics on campaign performance and deliver clear guarantees on brands only engaging with the highest quality influencers.”
Further information on the methodologies used can be found in the Buzzoole white paper The Battle for Authenticity: Fighting Influencer Marketing Fraud.