I’m running campaigns for a Russian brand expanding into the US market, and I keep hitting the same wall: my attribution numbers tell completely different stories depending on which market I’m looking at. A campaign that shows 3.5x ROAS in Moscow somehow looks like 1.8x in New York, and I can’t figure out if it’s a measurement problem or an actual performance gap.
The real issue seems to be that we’re not comparing apples to apples. Our Russian tracking setup measures things differently than what works for the US—different pixels, different customer journey lengths, different conversion definitions. When I try to pull everything into one dashboard, it’s like watching two parallel universes that refuse to communicate.
I’ve been experimenting with building a unified attribution model that accounts for these differences, but it’s slow and feels like I’m reinventing the wheel. I imagine others hitting this exact problem when they start working across both markets with different influencer networks.
How are you actually handling cross-market attribution when your measurement systems don’t naturally align? Are you standardizing everything to one framework, or keeping separate KPIs and just learning to read them differently?
This is such a real problem! I’ve seen so many partnerships fall apart because the teams can’t agree on what success even looks like. When I’m connecting Russian brands with US creators, we now insist on a pre-campaign alignment meeting specifically about metrics—it sounds boring, but it saves everything later.
One thing that helped: we started asking creators themselves how they track performance on their end. Turns out, micro-influencers have totally different insights than brand dashboards. They see real engagement patterns you’d miss otherwise. Maybe involving your influencer partners in the conversation could give you the ground truth you’re missing?
Also, have you thought about bringing in someone from the other market to audit your setup? I worked with a strategist from the US once, and having them literally walk through our Moscow process and then our New York process side-by-side was revelatory. Sometimes it takes that fresh pair of eyes to spot where assumptions are killing your numbers.
I deal with this constantly in our e-commerce business. The problem is deeper than just different tools—it’s that conversion behavior is genuinely different between markets. In Russia, we see longer consideration cycles and more price sensitivity. In the US, impulse purchases are higher but cart abandonment differs too.
Here’s what actually worked for us: we stopped trying to force one universal attribution model and instead built conversion probability models for each market using historical data. Then we normalized the ROAS to a base metric—we use CAC (cost per acquisition) as the common language. It’s not perfect, but at least we’re comparing real business outcomes, not platform metrics.
The key: you need 60+ days of clean data from each market before the model becomes reliable. Do you have that baseline yet?
One more thing—what’s your current attribution window? We found that US influencer conversions often show up 72+ hours later, while Russian audiences tend to convert same-day or next-day. That time gap alone was throwing off our comparisons by like 15-20%. Worth checking if your windows are set equally across both regions.
Also, which influencer networks are you working with in each region? That might matter too. US creators often use different platforms for promo links than Russian ones do, which could be throwing off your last-click attribution entirely.
This is exactly the kind of problem we solve for clients, so I see it frequently. The truth: most brands have terrible cross-market attribution because they’re trying to retrofit US tools onto Russian strategies (or vice versa).
What we do now is start with a partnerships-first mindset. Before we even launch a campaign, we align with influencers in both markets on how they’ll track, what UTMs they’ll use, and how results will be reported. It creates friction upfront, but eliminates the chaos later.
One tactical thing: if you’re working with US agencies or influencer networks, they’ll have their own measurement standards. Align with them early. Don’t try to force them into your Russian framework—instead, ask how they normally report and build a translation layer between that and your internal metrics.
Okay so I’m not on the analytical side like some folks here, but I can tell you what I see from the creator perspective: a lot of brands give us totally different tracking instructions for the US versus other markets. Like, one brand had me use a unique link for Russia but a QR code for the US. Then they couldn’t figure out why their numbers didn’t match up! 
I think the issue isn’t just your data—it’s that the creators themselves might be operating under different instructions. Have you made sure all your influencers (especially if you’re working with agencies in different regions) are using the exact same tracking setup? That could explain some of the variance.