ER is based on likes divided by followers. The number of posts considered varies based on the posting frequency. We usually try to consider two months, but sometimes we go back more than two months but never more than 500 pieces of content. Pinned posts are treated as regular posts. If they are not within 10 months or not part of the first 500 pieces, they will not be included.

The % of followers we consider not being real people i.e. bots.

We determine fake followers by scoring accounts' behaviour vs average Instagram user behaviour. We consider the profile photo, bio, followers, following, engagement behaviour, and account age amongst other things.

We also consider the ratios between these metrics (account age vs follower to the following ratio). These factors contribute to a score. If an account scores too far away from “average” they are marked as a fake account.

Fake likes are determined using the same methodology.

This metric compares the engagement rate of sponsored vs organic (non-sponsored) content.

Examples:

100% Paid post-performance means sponsored content performs exactly as well as organic content.

110% paid post-performance means an influencer’s sponsored content does 10% better than their average organic content.

Sponsored content is content that contains one of approximately 50 indicators that a post is sponsored. For example, if the content includes hashtags like #sponsored, #ad, #paid, #reklaam etc it will be marked as sponsored.

Content is disclosed using an in-platform disclosure feature (“Paid partnerships feature in Instagram for example).

Popular posts are the influencers' highest-liked posts among all the posts in the past 2 months.

In the PopularPosts for Instagram, they can be any type of content - a post or a reel. We don't have the type of content available as a field right now, but you can determine it by the type of data we have about the Popular Post. For example, if it has "views" it is a reel.

For recent posts, we don't have thumbnails, because the thumbnail URLs expire in about 6 hours on IG & TikTok. RAW API is the way to go if you want the recent posts' image thumbnails.

Thumbnails are available for popular posts because there we actually collect & store the content, so we can link you to the stored image.

This indicates the location of the influencer or the audience. To determine this, we analyze location tags, languages, descriptions, captions, bios and more.

We correct for travel by mapping the location consistently over time. Then, we determine the most common location the creator is in.

The average number is calculated based on the likes, comments and views gathered within the last two months, but no more than 500 posts in total. If the influencer does not post often, we may take the posts older than two months, but no more than 10 in total. The latest 150 posts are stored in our database.

Pinned posts are treated as regular posts. If they are not within 10 months or not part of the first 500 pieces, they will not be included.

Using a similar methodology as interests, influencer lookalikes display users that produce content around a similar set of topics.

To do this we analyze bios, captions, imagery, hashtags, mentions etc to create a map of the accounts topics. We then display other accounts that score similarly when put through the same process.

Audience lookalikes are based on overlapping audience demographics. If your influencer targets Young people in California, their audience lookalikes will target a similar demographic.

Gender estimation is determined by analyzing photos, captions and names. For example, a creator who has the first name “Sarah” and who posts photos of a woman's face will be categorized as female.

Age is determined by analyzing photos and profile images posted by the account.

Language is determined by analyzing the text the influencer uses in their captions, bio, etc.

You can see the Growth Rate of the creator on a monthly basis. The average likes and comments are shown monthly, based on the date when the content was posted. If someone posted something in January, we will count the likes etc as part of January’s statistics not taking into account when exactly the likes were added.

We have three brand affinities.

1. The influencers one.

2. The followers one.

3. The likers one.

All three are available via API.

Under profile, brandAffinity is based on the influencer's posts, comments and hashtags used.

This filter indicates how quickly the follower number of the creator is growing.

For example, Jenna Ortega (Star Of Netflix’s hit show “Wednesday”) has grown 150% over the last 4 months and therefore appears for the following search.

We have 3 layers of data.

Basic Data is updated bi-weekly, and Analysed Data is updated on a monthly basis. Each profile is updated on its individual cycle.

If a profile has more interest through our platform or API then the very basic data is updated more often, usually on a weekly basis. This is the reason why the engagement rate does not get updated as often as followers count and why they don't always match up.