I’ve been managing influencer campaigns for both markets for about two years now, and I keep running into the same problem: our Russian campaigns report metrics one way, our US campaigns report them differently, and when I try to consolidate everything into one story for leadership, it falls apart.
Right now we’re using separate dashboards. Our Moscow team tracks engagement and sales lift in rubles. Our US partner tracks conversions and LTV in dollars. On paper they look great individually, but when the CFO asks “is this actually working across both markets?” I don’t have a clean answer.
I know unified analytics exists, but I’m not sure if I should be pulling everything into one dashboard or if there’s a smarter way to structure this. Some people tell me cross-border attribution is the answer, but I’m not even sure what that means in practice.
Has anyone figured out a system where you can actually compare performance across these two very different markets without losing the nuance of what works locally? What does your actual workflow look like—are you consolidating data, or keeping things separate and just reporting them side by side?
I went through this exact situation last year. The key insight I had was that you don’t need one dashboard—you need one methodological framework.
Here’s what I started doing: I defined three tiers of metrics. Tier 1 is universal (reach, clicks, traffic). Tier 2 is market-adjusted (conversion rate, CAC, based on local costs). Tier 3 is regional only (things like engagement patterns that don’t translate).
Then I pulled everything into a single spreadsheet where Tier 1 metrics sit side-by-side, Tier 2 gets indexed to a common baseline (I use USD equivalent for cost), and Tier 3 lives in its own section for context.
The magic part: I calculate ROI as (Revenue - Ad Spend) / Ad Spend for both markets, but I track the revenue separately (RUB converted to USD at average monthly rate, not spot rate—this reduces noise). When I present to leadership, one slide shows the consolidated ROI story, and another shows the regional breakdown.
What helped most was talking to our finance team first to agree on how to treat currency fluctuations. That conversation alone saved me weeks of rework.
One dataset is the right move, but you need to set up your attribution model first. Here’s why: if you’re running simultaneous campaigns in Russia and US, they’re probably overlapping in awareness or intent for certain audiences (especially if you’re targeting diaspora or looking at cross-market brand lift).
I’d recommend this approach: use a unified data warehouse (Amplitude, Mixpanel, or even a consolidated Google Sheet if you’re starting small) where every transaction has both a market tag and a campaign source tag. Then run attribution backwards—instead of asking “did this campaign convert,” ask “what was the first touchpoint, last touchpoint, and all the touchpoints in between for this customer?”
Once you have that, ROI becomes trackable per market AND per campaign, even if they’re in the same dataset. You’ll see overlap and nonlinear effects.
The US side should be straightforward (most US brands already have this). The Russian side might be trickier if you’re working with local partners who report quarterly instead of daily. I’d set up a reconciliation process for that.
We faced this when we started targeting Russian-speaking audiences in the US. My advice: start with one dataset, but don’t try to be perfect from day one.
What actually worked for us was building a simple spreadsheet first (campaign name, market, spend, revenue, days running, cost per acquisition) and seeing where the real gaps appeared. It took three months of manual data entry, but it forced me to understand the data quality issues before I invested in a “proper” solution.
Turned out our Russian partners were using different attribution windows than our US team. Once we standardized that conversation, everything else became easier.
Honestly though, if you’re serious about scaling this, you probably need someone dedicated to data ops. Managing two markets and two reporting systems is a job itself.