Jan 29, 2026
How to measure influencers to see who actually drives sales
Sam Faillace
,
VP of Marketing
Connect with Sam
You might be...
…thinking about increasing your TikTok influencer spend by $300,000. You’ve got $2 million left in your YouTube budget for the year. Instagram creators are posting great content. But your team needs to know which creators drive revenue — not just likes and ad clicks — and who you should invest in next.
Across dozens of influencer programs, we see two consistent failure modes.
First, teams scale by volume, not validation. They add more creators without confirming which ones actually drive incremental business.
Second, they measure each influencer by affiliate link clicks and engagement and then attribute additional revenue accordingly, instead of measuring whether each one actually inspired sales. This typically leads to over-crediting of bigger influencers and under-crediting of others.
Meanwhile, the halo effect of the average influencer’s post is much bigger than what click-tracking will show you. Your creators are probably a lot more influential than you give them credit for.
Most teams scaling influencers run into the same wall: they see everything except what matters. Clicks, likes and affiliate sales tell one story, but not the one that explains growth.
The real story hides underneath: Which creators create net-new demand?
Here’s the system we use to reveal the answer.
P.S. Want to find the influencers who actually drive sales? Here's a quick one-page guide.
The problem to solve: Which creators drove incremental revenue?
In 2023, Paramark empowered a global language learning app with $100M ARR to test, validate and quadruple their spend on influencers as they expanded into East Asian markets.
When they came to us, they were using clicks on affiliate links, impressions and engagement to measure success.
But attribution collapses when you invest in creator-led social. UTMs get stripped, view-through is unreliable and purchases might happen days later. Most brands either over-credit influencers or under-credit them entirely.
Clicks are one of the least predictive signals of actual lift.
High engagement often correlates with entertainment value, not persuasion. Some of the most clickable creators produce the least incremental revenue, because they attract audiences who would never convert or who were already primed to purchase.
We set out to measure influence, not just eyeballs.
Try our incrementality calculator →
When we measure influencers, we aim to answer these three questions for any brand:
Which content formats sell best?
What’s the true iROAS of each creator?
Where should I put my next $50K of budget?
The solution: How incrementality cuts through the noise
Working with the marketing team at the language learning app, we started by grouping their influencers into three buckets: mega, macro and micro. As these creators posted, we populated a spreadsheet with each post’s spend and engagement rate after 30 days.
Then we fed the data into our custom marketing mix model (MMM) to correlate it with app trials and paid sign-ups.
We unlocked the discovery that influencers were this brand’s second-best channel behind Meta.
The model gave them the confidence to double their influencer spend – two years in a row.
Our practical 5-step creator incrementality workflow
Group creators by format (UGC, scripted, demo, lifestyle) or type (audience size).
Set up a lightweight pre-post test:
Define your measurement window (e.g. a 4-week view).
You don’t need a perfect geo test. You can begin with creator-level off/on periods to generate directional lift signals.
Measure net-new sales, not clicks.
Use your experiment readout to isolate causal lift for the cohort you tested.
Then, use MMM to estimate ongoing, channel-level incrementality over time as your influencer program scales.
Rank creators or groups of creators by iROAS and content type performance.
You’ll almost always find a “hero creator” cluster hiding in plain sight.
Scale horizontally by creator archetype, not individual creator.
This is where teams get 2–3x ROI gains with no increase in budget.
The mini data story
Here’s a real-looking scenario:
Creator | Spend | Attributed Sales | Incremental Sales | iROAS |
@JessEats | $15K | 150 | 120 | 8.0x |
@StyleMara | $15K | 200 | 40 | 2.6x |
@TechDrew | $15K | 60 | 10 | 0.6x |
What this means: Jess’s content drove the most incremental lift, even though Mara appeared to outperform her on attributed sales. This is why incrementality matters.
How to shine a light on influencer measurement in the next 30 days
The creator who “looks good” isn’t always the creator who sells. Incrementality finds the difference.
If you want to improve your influencer measurement in the next 30 days, run a holdout test.
Then, shift 20 to 40% of your influencer budget to top-performing creators and test 2 or 3 new creators who share similar traits. Re-measure after 30 days and optimize again.
Engagement and clicks ≠ revenue. Touch-based models overvalue detectable touches, not causal ones.
Most teams scale influencers by adding more creators. But the teams that win scale by discovering the few creators who truly shift demand, and then replicating what makes them work.
Incrementality is how you find your heroes.
Talk to Paramark’s growth advisors about creator measurement →
