I’ve been running influencer campaigns for three years now—mostly in Russia, but for the last year I’ve been trying to scale to the US market. And I keep hitting the same wall: the metrics don’t translate.
In Russia, I can track conversions pretty cleanly. I know my CAC, my ROAS, I can see the exact moment someone clicked an influencer’s link and bought something. But when I started working with US creators, everything fell apart. Different platforms, different tracking capabilities, different attribution windows. I’d give the same brief to a Russian influencer and a US influencer, and I’d get back completely different performance data.
The worst part? I couldn’t figure out if that was because the campaigns actually performed differently, or if I was just measuring them wrong.
I’ve tried stitching together data from multiple sources—UTM parameters, Google Analytics, the influencer’s own dashboards—but it’s exhausting and the numbers never quite add up. I know I’m not alone in this. Every time I talk to other marketers doing cross-border work, they mention the same frustration.
Has anyone here actually solved this? Do you use a specific framework or tool that lets you compare influencer ROI across markets without losing your mind? I’m specifically interested in how you handle attribution when creators are posting to different platforms and using different conventions.
I’ve been tracking this exact problem for about two years now. The issue isn’t really the platforms—it’s that US and Russian influencer audiences have fundamentally different conversion behaviors. Russians tend to convert faster and closer to the content drop. US audiences need more touchpoints.
What I started doing was building separate attribution models for each market instead of trying to force one unified model. For Russia, I use a 7-day window with last-click attribution. For US, I’ve extended to 14 days and I weight assisted conversions more heavily.
But here’s the real insight: once I stopped trying to make the numbers comparable and instead looked at them as two different stories, the strategy actually improved. In Russia, I optimize for immediate impact. In the US, I’m now building for longer funnel engagement. The ROI numbers look different, but they’re both real.
I track five core metrics for both markets: engagement rate, click-through rate, CAC, ROAS, and what I call “assisted revenue”—sales that happened within 30 days but weren’t the direct last-touch. That last one is what changes everything.
One more thing—I started asking influencers in each market to use unique promo codes instead of relying only on UTM parameters. It adds friction for them, but the data I get back is incomparably cleaner. Promo codes give me direct transaction-level attribution. UTMs are good for top-of-funnel awareness, but they’re garbage for ROI measurement when you’re comparing across markets.
The flip side is that microscopically, you’ll see that some content drives awareness that converts weeks later through organic search. That’s where the unified framework would help you—but I haven’t cracked that part yet.
You know what? This is such a common pain point, and I think the real bottleneck is that most brands aren’t having structured conversations with their influencers about measurement from the start. I’ve noticed that agencies that do specify their tracking requirements upfront—UTMs, promo codes, timing of posts, expected engagement bands—end up with way cleaner data.
I’d love to see more brands and creators have these conversations earlier. It’s not sexy, but it matters. When I’m putting together a partnership, I always ask: “How will we measure success, and what data will you share with me?” If a creator can’t articulate that clearly, it’s a flag.
This is a reality I deal with constantly. Here’s what I’ve learned: the fragmentation isn’t going away, so you have to build redundancy into your measurement system. I use three data sources in parallel: platform-native analytics (Instagram Insights, TikTok Analytics), my own UTM + promo code tracking, and third-party attribution tools like Branch or Adjust.
When all three sources roughly agree, I trust the number. When they diverge, I investigate. Usually it’s because the audience composition is different or the content resonated differently than expected.
For cross-market comparison specifically, I’ve stopped trying to normalize to a single metric. Instead, I report market performance separately but contextualize it: “Russia spent $X and generated $Y in direct revenue plus $Z in attributed awareness value. US spent $A and generated $B in direct revenue plus $C in attributed awareness value.”
Your board might not love that you can’t say “both markets have the same ROI,” but it’s honest. And honestly usually beats false precision.
I’ve been wrestling with this for my tech startup. We’re based in Moscow but going hard on the US market, and influencer marketing is one of our primary channels.
What finally helped me was realizing that I was trying to measure the wrong thing. I was obsessed with immediate ROI—the transaction within 30 days. But for SaaS products (and I suspect for a lot of other things), that’s not where the real value is. The real value is long-term LTV.
I started tracking three cohorts separately: (1) direct purchasers within 30 days of influencer content, (2) people who engaged with the content but converted 31-90 days later, (3) people who never converted but became paying users of our free tier or engaged with our community.
Turns out, for my US market, cohort 2 and 3 are where most of the real value is. My Russia-first instinct was completely wrong for that market. Now that I’m measuring it properly, my ROI looks “worse” in the first 30 days but way better over a 12-month window.
Here’s a hot take: most brands are measuring influencer ROI wrong even within a single market, let alone across markets. They’re obsessed with last-click attribution, which assumes that the influencer post is the only touchpoint that matters. It never is.
What we do at the agency is build a full customer journey map before launch. We ask: What’s the awareness stage? What’s the consideration stage? Where does the influencer fit in that funnel? Then we measure contribution at each stage, not just conversion.
For cross-market work, you need to be even more intentional because the funnel shapes are different. In Russia, the funnel is usually shorter and narrower. In the US, it’s often wider and longer. Once you map that, the attribution becomes much clearer.
Do you know your market-specific funnel shapes? That’s the starting point I’d recommend.
From my side as a creator, I can tell you that brands often ask me for metrics I literally cannot provide. They want data about swipe-ups, link clicks, all this stuff—but Instagram and TikTok don’t always give that data to creators anymore. It’s really limiting.
What I can reliably do is drive my audience to a promo code, track that in my own analytics, and let the brand know how many people used it. That’s been the most honest way I’ve found to measure impact.
I think part of the issue is that brands expect creators to be data engineers, when really we’re just content people. If you want clean attribution data, you have to build the system yourself—don’t rely on the creator to do it.