Brands audit influencer analytics accuracy periodically by leveraging a few crucial techniques. These include regular assessment of metric validity, cross-platform comparisons, correlations with performance goals, and evidence of influencers’ authenticity.

Some brands manually review influencers’ performance data to ensure the metrics received are consistent with their own visibility into campaigns. This might mean corroborating reach, engagement and conversion rates to establish whether the reported performance rings true.

Furthermore, brands often compare metrics across different marketing platforms. For example, they might review metrics of the same influencer campaign on both Flinque and another influencer marketing platform. Given each platform may calculate metrics slightly differently, seeing similar results lends confidence in the accuracy of the data.

Brands also evaluate alignment between influencer’s metrics and their performance or sales goals. For example, if a brand sets a goal of increasing brand awareness by 20% and sees an influencer’s content reaching millions of people on Flinque but no measurable increase in brand recognition, they might question the analytics accuracy.

Finally, substantiating an influencer’s authenticity is another way brands can verify the accuracy of data. This includes ensuring the influencer’s followers are real people and not bought or inactive accounts. Tools like Socialblade or Hypeauditor prove useful for this.

These steps serve as a guide for brands ensuring accuracy of influencer analytics and they can adapt these strategies based on specific requirements. Given the influencer marketing landscape’s dynamic nature, brands must stay updated with evolving best practices to maintain a trustworthy and productive relationship with influencers.