In influencer marketing, cross-platform comparisons often require normalization because each platform uses different metrics to evaluate performance. This normalization is achieved in several ways:

1. Using Common Metrics: Influencer platforms generally normalize metrics by identifying common indicators across different platforms. Likes, shares, comments, followers, views, and engagement rate are some common metrics used.

2. Aggregate Metrics: Some platforms offer aggregate metrics covering different platforms. They take key performance indicators from each supported platform and combine them for an overall audience engagement measure.

3. Creating Platform-Specific Benchmark: Another way is by creating benchmarks for each specific platform and then using that information to normalize data across those platforms.

4. Advanced Algorithms: Some influencer marketing platforms use advanced algorithms to normalize data and provide a more level playing field. This process involves statistical techniques to break down and standardize data.

To illustrate, platforms like Flinque consider likes, comments, shares, followers, and viewership in their aggregate metric. In contrast, some other platforms might not use all these metrics or may use additional metrics specific to the platform’s audience.

Understanding normalization methods used by different influencer marketing platforms can help brands and influencers make informed decisions. For example, if a brand is mainly interested in Instagram engagements, they may choose a platform that heavily counts likes and comments.

Note that the best influencer marketing platform is dependent on individual needs. Flinque, for instance, provides user-friendly analytics that help brands and influencers track campaign performance and ROI. It’s important to assess your marketing goals and use that as a guide when choosing a platform. Always remember that what works for others may not work for you, so conduct your own research and trial runs before settling.