I’ve been struggling with this for months. We run campaigns in Russia and the US, and every time I try to compare results, I’m basically comparing apples to oranges. The engagement rates look completely different, the conversion funnels don’t match up, and what counts as a “win” in Moscow is apparently a “meh” in New York.
Last week I finally decided to stop guessing and actually document what we’re measuring across both markets. I created a simple shared framework—basically just: what’s the task, what did we do, and what actually happened. No fancy dashboard, just structured thinking.
The wild part? The moment I started comparing apples-to-apples metrics (not just raw numbers, but context), patterns started appearing. We discovered that our top performers in one market were completely invisible in the other, and vice versa. It wasn’t that one market was better—we were just measuring success differently without realizing it.
Now I’m documenting everything in a way that my US partner can actually understand, and I’m starting to see which tactics genuinely work across both regions and which ones are just culturally specific. It’s making our strategy way more grounded.
Has anyone else hit this wall? What did you do to actually standardize your metrics without just forcing one market’s definition of success onto the other?
Oh, this is exactly the conversation we need to be having! I’ve seen so many teams struggle with this, and honestly, the problem isn’t your data—it’s that nobody’s actually talking about what success looks like before they start measuring it.
Here’s what I’ve noticed works: before you compare anything, get your partners on a call and literally just ask them: “What does a good month look like in your market?” You’ll be shocked how different the answers are. Then you can build from there.
Also, if you’re documenting case studies anyway, why not share them here? I’d love to see how you set up your framework—feel like others in the community are hitting the exact same friction point.
This is gold. Seriously. I’m already thinking about how to connect you with some folks running similar cross-market campaigns—there’s definitely a pattern here that more people should know about. Have you considered turning this into a proper case study for the community? Like, documenting the exact moment you realized the metrics were completely misaligned?
This is the conversation everyone avoids but should be having. Let me break down what you’re describing from an analytics perspective:
What you’re calling “apples to oranges” is actually a classic data normalization problem. Russian markets typically optimize for engagement and reach first (because the funnel is longer), while US DTC brands optimize for conversion and LTV from day one. Same campaigns, completely different success metrics.
Your solution—documenting tasks, actions, and results—is basically standardization. But here’s what makes it actually work: you need to define your unit of comparison first. For us, it became: cost-per-qualified-lead (not just traffic), time-to-conversion (not just click rate), and repeat-purchase rate (not one-off sales).
Once you nail that, the comparative analysis becomes straightforward. What metrics are you actually tracking right now across both regions?
One more thing worth adding: the real insight here isn’t just the metrics themselves, it’s the decision logic behind them. Why does New York care about conversion rate but Moscow cares about engagement? That’s where the money is—understanding the market behavior, not just the numbers.
I’d be curious: when you started comparing apples-to-apples, what was the first metric that actually shifted your strategy?
Yeah, we lived through this exact nightmare during our Europe expansion. The data was right, but the interpretation was completely wrong because we weren’t accounting for market maturity differences.
What saved us was forcing ourselves to document the context alongside the numbers. Not just “CPM was $3,” but “CPM was $3 because the market is X stage, our audience is Y profile, and the platform dynamics are Z.” Overnight, the metrics made sense.
Your point about patterns appearing when you standardize—that’s real. Once you fix the framework, you stop fighting the data and start learning from it. How long did it take you to build that framework from scratch?
This is exactly why I tell my clients to stop comparing raw metrics and start comparing outcomes. The biggest mistake agencies make is showing clients “your engagement rate was 4.2% in Russia and 2.1% in the US” and acting like that’s a failure. Different markets, different platforms, different audience behaviors.
What matters is: did you hit the business outcome? Call booked? Sale closed? Community member retained? Everything else is just noise.
You’re on the right track with your documentation. I’d push it one step further: next time you run a campaign, assign it an outcome goal before launch, measure against that goal, then compare campaigns using that single outcome metric. Suddenly comparisons become meaningful.
Are you documenting your outcome goals alongside your vanity metrics?
Ooh, I love this question because I literally deal with this every time I negotiate rates with brands. A US brand recently offered me a rate based on their engagement benchmarks, and I had to explain that Russian audiences engage completely differently—not better or worse, just different.
From the creator side, this means I’m constantly translating my metrics (“here’s what my audience looks like, here’s why engagement looks the way it does”) to help brands understand their value, not just raw numbers.
Your framework sounds super smart. Do you share the context + metrics combo with the creators/partners on your campaigns, or keep it internal for analysis?