I’ve been running influencer and UGC campaigns across Russian and US audiences for about two years now, and honestly, the hardest part isn’t finding creators or managing timelines. It’s convincing leadership that what we’re doing actually moves the needle when you’re operating in two completely different markets.
When I started scaling from Russian-speaking audiences into the US, I quickly realized that the metrics we tracked domestically didn’t translate. Engagement rates, CPM, even conversion paths—they’re all different. Our C-suite kept asking, “So what’s the actual ROI?” and I couldn’t give them a straight answer because I was mixing in too many variables.
What changed was getting access to structured case studies and success stories from both markets. I started documenting wins from US-based influencer partnerships side-by-side with Russian campaigns, and I stopped trying to blend them into one narrative. Instead, I showed the C-suite exactly what ‘win’ looks like in each market—different benchmarks, different timelines, but same strategic framework.
I also leaned into cross-border partnerships to validate results. When I could show that a US-based influencer partner had run similar campaigns with comparable brands, I had real proof points. Not assumptions. Real data.
My question: what metrics do you actually present to your leadership when you’re running campaigns across two markets? Are you combining them into one ROI story, or are you keeping them separate and building a portfolio approach? I’m curious if anyone else has hit the wall I hit and what actually worked to break through it.
This is exactly the problem I’ve been wrestling with. The issue is that most influencer ROI models assume a linear funnel, but bilingual campaigns aren’t linear—they branch.
Here’s what I’ve started doing: I track three separate metrics stacks. One for awareness (reach, impressions, share of voice in each market), one for consideration (engagement quality, audience overlap, sentiment), and one for conversion (actual attributed sales, repeat purchase rate by market source). Then I tier them: awareness metrics drive the lower-funnel metrics, not the other way around.
The game-changer was setting market-specific benchmarks. Russian influencer audiences have different trust patterns than US audiences. Average engagement in Russian TikTok is higher, but conversion intent is different. Once I showed the C-suite that we’re not comparing apples to apples, and that our ‘lower’ US engagement actually drove higher purchase intent, they stopped asking “why aren’t we hitting Russian metrics in the US?”
Also—and this matters—I started using cohort analysis. For each campaign, I track the creators’ existing audience composition and compare it to what we needed. When a creator’s audience was 60% our target demographic vs. 40%, I could explain upfront why the numbers would look different. No surprises at reporting time.
What attribution model are you using across borders? I’m guessing you’re running into UTM challenges when traffic bounces between markets?
One more thing I want to add—cost structure. A lot of people forget that creator rates are wildly different between Russia and the US. A mid-tier influencer in Moscow costs maybe 30-40% of what you’d pay a comparable creator in LA. When I show the C-suite ROI, I always include cost per acquisition by market, not just overall CAC. That changes the narrative completely.
A $500 campaign with a Russian creator might generate $2,000 in revenue (4x ROAS). A $2,000 campaign with a US creator might generate $8,000 in revenue (also 4x ROAS). Same efficiency, wildly different absolute return. The C-suite cares about both—absolute return for growth, and efficiency for scaling.
Have you modeled out cost-per-acquisition by market? That’s the number that usually makes the pitch stick.
You’re touching on something critical here, but I think you might be overcomplicating it. Here’s the perspective from managing larger US-based campaigns:
Your C-suite doesn’t actually want two separate ROI stories. They want one narrative with two supporting pillars. Think of it as: “Here’s how we’re building a repeatable playbook that works across geographies—and here’s the proof.”
Instead of showing Russian metrics vs. US metrics as separate wins, show them as validation of your process. “We tested this creator type in Russia. Here’s what worked. We applied those learnings to the US. Here’s the result.” It frames bilingual campaigns as iterative learning, not as two different experiments.
The metrics that move the needle with C-suite? Payback period and repeat customer rate. Not impressions. Not even initial conversion—repeat purchase. Because that proves you’re not just getting attention; you’re building a customer that sticks. And that works across borders because repeat behavior is actually consistent.
Set your baseline on repeat purchase rate by market, show how influencer-sourced customers compare to your other CACs, and you’re done. That’s the story.
Are you tracking repeat purchase rate by traffic source, or are you still stuck on first-purchase attribution?