Blog post

EAS explained: how the metric we developed solves a key influencer marketing challenge

7 Dec, 2020
EAS explained: how the metric we developed solves a key influencer marketing challenge

It’s late. The office (or home office nowadays) is already in darkness. You’re tired. And you’ve just been set a task to find 25 micro influencers who know vegan food inside out and might have a side interest in running. 

Better get the kettle on.

If you’re familiar with the above situation then it’s likely you know what’s coming next as well. 

First there’s the challenge of finding influencers who broadly match the brief to begin with. No mean feat in its own right. You’ll need to spend some time browsing common vegan and running hashtags, combing through accounts and picking out the ones who qualify as influencers. Even this step can be hours of work.

Then there’s the next phase; assessing those you’ve found to find the most effective influencers. In short: weeding out the pretenders to leave yourself with those who are going to have the most impact on your campaigns.

And this is where things get really tricky.

How can you judge, just by browsing Instagram profiles, who is going to have the most influence for you, on your particular campaign? How are you judging success? By reach? By buying behaviour, or actual sales? How can you link that to what you can see on an Instagram profile?

Follower counts are the most visible metric you can use, but is there really any link between number of followers and performance in an influencer marketing campaign? How can you tell how engaged those followers are?

You could work out engagement rates fairly easily, by looking through any given influencers last few posts. But, again, how does that relate to your specific campaign? Just because your vegan influencer got a high level of engagement when they visited a local vegan deli, will they get the same level when they post about your vegan energy bar for runners?!


Introducing... Engagement Affinity Score (EAS)

Solving the above challenges are absolutely at the core of what we do. 

We spent four years working towards solving the challenge of finding niche micro influencers for any individual, specific campaign.

The answer is the Influence Network platform, but behind that platform the really clever bit is our Engagement Affinity Score (EAS) system.

EAS uses AI to measure the potential an influencer has to receive engagement on their posts, whilst also measuring whether or not the influencer has a real affinity with the individual brand or campaign being planned for.

The EAS algorithm uses the past experience of the platform to find and give an EAS to each individual influencer, but it also accounts for a range of factors on a campaign-by-campaign basis.

So, of course, the algorithm automatically takes account of follower levels. But we know follower levels aren’t the be-all-and-end-all of influencer marketing success.

So EAS also factors in things like an influencer’s comment to like ratio.

And it uses natural language processing analysis, so that we can see if our vegan influencers ever also find themselves in conversations about running and how they talk running. Are they a ‘God, I hate running’-type of person or a ‘running gets me going in the morning’-type of person. Both options would return a result for ‘running’. We factor in how running is being spoken about.

And we track the generation of buying signals and how relatable an influencer is using a relatability index. And we analyse positive, negative and neutral sentiment analysis (like the above running example) including emoji sentiment analysis. And the list goes on.

The AI factors in all of this and generates an EAS for each influencer. The higher the score, the more aligned the influencer is with your brand or campaign and the higher the chance that they will generate positive rates of engagement on their promotional posts. 

The platform carries out EAS calculations at the campaign level for every campaign, so an influencer who is more suitable for a particular brand/product and campaign will receive a higher EAS for that campaign specifically and will be rescored for every campaign before being shortlisted by the system again.

Every time our platform is used (which is a lot), the AI learns from what it finds and factors this into future calculations, so we’re always improving how we score the influencers we find. Discovery of those influencers, by the way, also happens automatically, through the power of the AI, so even your first task is completely covered off for you.


Influencer discovery, campaign success

We love EAS because, paired with our automatic influencer discovery, we think it ends those cold late nights for you, trying to find micro influencers and guessing at whether they’ll be highly successful or not.

EAS is unique to the Influencer Network platform and we’d be happy to show it to you in a little more detail - why not book a demo? Just drop us a note on

Written by Harriot Rockey

COO, Influence Network

Influence Network is an influencer platform which identifies the most aligned micro-influencers from the entire social web, then rapidly deploy and manage campaigns at an unprecedented scale, before reporting on trackable engagement and ROI. We’re the Double-Click of influencer marketing and we’re here to solve your influencer problems. Sound interesting? Get in touch on INFO@INFLUENCE.NETWORK or 0203 918 8582


Harriot Rockey


Book a platform demo

Click the button below to request a demo with a member of our team.

© 2023 Influence Network. Registered in England and Wales: 10815710

Registered Office: 20-22 Wenlock Road, London, N1 7GU

© 2023 Influence Network.

Registered in England and Wales: 10815710

Registered Office:

20-22 Wenlock Road, London, N1 7GU