Influencer Marketing Works. The Metrics Don’t.
Why spend keeps rising, what brands actually look at, and where measurement is heading next.
Hi friends!
Hope you are all staying warm out there.
This week we are doing a deep dive on what influencer marketing metrics actually mean and how the industry can be improve by working off a different framework.
We are also taking a look at why Liquid Death keep crushing it and how the new content format, micro-dramas is taking off.
No time to waste. Let’s jump right in.
(January 20th)
📈 Influencer Marketing Keeps Growing Despite Measurement Gaps
Influencer marketing spend is still climbing, even as the industry admits it doesn’t have clean measurement standards. New data from Kantar shows brands plan to increase investment in creator partnerships in 2026, despite ongoing challenges around attribution, comparability, and consistent reporting.
What’s notable is the tolerance for ambiguity. Brands appear willing to fund creator marketing based on perceived effectiveness and cultural relevance rather than precise ROI models. In a landscape where attention is harder to buy through traditional channels, imperfect data is proving less of a blocker than expected.
I think we might have cracked a better way to do it. More on this in the Trend watch at the end.
⏱️ YouTube Partnerships Need Longer Attribution Windows
YouTube creator partnerships are taking longer to show measurable impact than brands often expect. A new analysis suggests that a 90 day attribution window is more realistic for YouTube campaigns, especially for higher-consideration categories where discovery and conversion are spread over time.
The finding highlights a mismatch between short-term performance expectations and how long-form content actually works. Unlike feed-based platforms, YouTube content continues to surface weeks or months after publication, pushing value further down the timeline than most campaign reporting allows.
YouTube Partnerships mature at 90 days
🎭 TikTok Bets on Micro-Dramas as a New Content Format
TikTok is experimenting with scripted micro-dramas through a new app called Pine Drama, signaling interest in short-form storytelling that sits somewhere between social video and episodic TV. The format is designed for quick consumption, serialized viewing, and frequent returns rather than one-off virality.
The move suggests TikTok is looking beyond creator-led content alone, testing whether narrative formats can drive repeat engagement and new monetization paths. It’s another attempt to stretch how entertainment functions inside mobile-first platforms.
🧠 Brand Move of the Week
Liquid Death Keeps Treating Marketing Like a Product
Liquid Death continues to operate as if marketing itself is the product. Instead of separating brand building from sales, the company uses social content, stunts, and packaging as distribution tools that move attention and volume at the same time. The strategy isn’t about chasing trends. It’s about staying legible and entertaining inside feeds that punish hesitation.
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What stands out is consistency. Liquid Death doesn’t toggle between “serious” and “playful” depending on the channel. Every activation, from social posts to limited-edition drops, follows the same logic. Be instantly recognizable. Be culturally fluent. Make the product part of the joke without undercutting its utility. That repetition is doing the work most ad spend used to do.
The result is a brand that rarely has to explain itself. Social becomes the primary surface, retail becomes the payoff, and paid media plays a supporting role rather than carrying the message. Liquid Death isn’t optimizing for campaigns. It’s optimizing for momentum, and letting distribution compound over time.
🔭 Trend Watch
How to predict creator outcomes in 2026?
There has to be a better way!
If influencer marketing couldn’t be measured at all, investment wouldn’t be growing. Instead, Kantar reports that brands plan to increase creator spend in 2026—despite ongoing challenges with attribution and standardization.
That tells us something important: brands aren’t flying blind. They’re operating on imperfect but persuasive signals.
Engagement rate still shows up in reports, but few experienced marketers believe ER% explains outcomes. A like can mean entertainment, agreement, irony, or intent—and those are not interchangeable.
In practice, smart brands already rely on richer judgment:
Reading comment sections for intent and objections
Favoring creators whose audiences ask questions and save content
Repeating partnerships where response quality feels right, even without clean numbers
This works—but it doesn’t scale, and it’s hard to explain.
The Data Isn’t Missing—It’s Fragmented
The industry isn’t data-poor. It’s poor at making sense of the data.
Every campaign already generates useful signals:
Comments reveal sentiment and purchase readiness
Saves and rewatches signal future intent
Topic consistency shows real authority
Link behavior hints at commercial comfort
Momentum inside micro-communities often beats raw reach
Individually, these signals are noisy. Together, they’re directional.
What looks like “tolerance for ambiguity” is actually brands making educated bets—just without a structured way to do it.
Where This Is Going
The next unlock isn’t perfect attribution. It’s using AI to aggregate the signals we already trust informally and turn them into forward-looking predictions by looking at user behavior.
Not “Did this creator perform?”
But “How likely is this creator to perform for this brand, right now?”
That’s what we’ve been building over the last few months.
We’re currently beta-testing this new way to evaluate creator–brand fit that goes beyond followers and engagement rate, focusing instead on audience behavior and conversion readiness.
If you want early access or would like to pressure-test it with real creators, reply here and I’ll share next steps.