One of the great misperceptions of influencer marketing in 2019 is that measurement is very difficult and predicting real business results before the campaign starts is impossible.

We've already outlined at length 25 Ways to Measure Influencer Marketing as well as crafted an online Master Class you can take on 9 Ways to Measure Influencer Marketing That Will Impress Your C-Suite. Given that, I won't spend time in this post on how to measure influencer marketing. Instead, I'll focus on how to predict the results of influencer marketing in advance.

Neither Do I!

Why You Can't (Currently) Predict Influencer Marketing Results

Not being able to predict the outcome of your influencer marketing program is not a limitation of the measurement tools currently available. Instead, it's a limitation in the construction of your program.

Most influencer marketing programs find influencers, engage them via contract to create sponsored content and then track if they do their assignments. Some track the clicks on links from influencers but are typically underwhelmed with the results.

Here's what's missing. Brands that take control of their influencer marketing programs with full syndication strategies can predict what the outcomes are going to be. At Carusele, our influencer marketing system even guarantees specific results, such as a minimum number of visitors to a specific web page.

Content Analysis Strategy Is Key

Carusele influencers have created tens of thousands of pieces of content for leading brands and retailers and we analyze the performance of each and every piece. What we learned is one of the dirty little secrets of influencer marketing:

A campaign that can't identify those outstanding pieces of content and elevate only those to people likely to buy isn't a predictable campaign. But a campaign that can do that can predict results in advanced from influencer marketing programs.

The best programs pull in automated data (real time counts of likes, comments, shares, engagement rate, etc.) and then supplement it with hand scoring to ensure the engagements are both real and brand meaningful.

For example, let's say the automated data returns a piece of content for a food brand that has very strong engagement rates. But during hand scoring, the influencer marketing program manager notices that nearly all the comments compliment the influencer's blouse. In that case, that piece of content is not one of the top performing pieces.

Syndication Strategy is the Next Step

By syndicating only the highest performing content, we gain cost efficiency. Unlike all other types of advertising where the cost of the inventory doesn't change based on the quality of your ad, social media algorithms favor high-performing content. As a result, costs such as CPM or CPC are lower for high quality content than for average or below average content.

Knowing that, and using historical benchmarks, it becomes entirely possible to predict influencer marketing metrics, such as true views of content (please don't even consider "max potential impressions") and/or the number of website visitors you will receive on a given page for a given program.

Rebuild Your Influencer Marketing Framework

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If being able to predict (and then drive) real business results from influencer marketing sounds awesome (and, really, it is) the obvious next step is rebuilding your influencer marketing programs to allow it.

If you need help with that, just contact us anytime.