Campaigns
How to measure influencer campaign performance beyond likes
Likes are the easiest metric to drop into a campaign report, and they're close to the least useful one for deciding whether to work with a creator again. A like requires almost no commitment — it tells you a post didn't actively repel anyone, and not much more than that.
Matching the metric to the actual campaign goal
| Campaign goal | Metric that actually matters | Why likes fall short here |
|---|---|---|
| Awareness | Reach, saves, shares | Likes don't measure spread beyond the immediate audience |
| Consideration | Comments, click-through rate, saves | Likes don't capture genuine interest or intent to learn more |
| Direct sales | Code redemptions, tracked link conversions | Likes have essentially no correlation with actual purchases |
| Brand sentiment | Comment tone, share context | Likes say nothing about how the audience actually felt about it |
A campaign report that leads with "the post got 4,000 likes" without specifying which of these goals it was actually working toward tells you almost nothing useful about whether the campaign succeeded on its own terms.
Why checking the matched metric changes the verdict
A sponsored post can have modest likes and still be a genuine home run if the goal was awareness and it drove strong reach and shares beyond the creator's normal audience — likes were never the right yardstick for that campaign to begin with. Conversely, a post with a large number of likes can still be a real failure if the goal was direct sales and the tracked code saw almost no redemptions — the likes measured something the campaign wasn't actually trying to achieve.
A basic post-campaign checklist
1. Confirm what the original goal actually was. Awareness, consideration, or sales — write it down before the campaign launches, not after, so there's no temptation to retroactively pick whichever metric looks best.
2. Pull the metric that matches that goal specifically, not the easiest one to find in the platform's summary view.
3. Compare against the creator's own typical baseline, not against a different campaign or a different creator's numbers — that's the only fair comparison, since audiences and content styles vary too much for cross-creator comparisons to mean much.
4. Note qualitative signal too — comment tone and sentiment matter for brand campaigns even when they don't show up in a single clean number.
Where this analysis actually happens
Pull a campaign's performance data into mayy.ai and ask which posts actually moved the metric that mattered for that specific campaign's goal — not just which ones racked up the most engagement overall, which is a different and often misleading question.
A campaign that "did well" by the easiest available metric and a campaign that actually hit its real goal aren't always the same campaign — and the gap between those two verdicts is exactly what a likes-only report reliably hides from you.
See this for your own accounts
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