I’ve been working on this for about eight months now, and honestly, it took me way longer than it should have to figure out how to properly analyze our influencer campaign results across markets.
Here’s the thing: we have a Russian e-commerce brand that’s been expanding into the US market, and our influencer campaigns look completely different when you put the metrics side by side. In Russia, we get decent engagement on Instagram and VK, but when we run the same type of campaign in the US, it’s like we’re speaking a different language—literally and figuratively.
The real pain point for me was that I couldn’t figure out which metrics actually meant “success” when comparing the two markets. Is 5% engagement in Russia equivalent to 2% in the US? Are we even measuring the same thing? I was pulling data from different platforms, different time zones, different audience expectations, and it was a mess.
What finally helped was building a framework where I could standardize the data and then get input from people who understood both markets. I started collecting performance data in one place, normalizing it for platform differences, and then actually talking to people who had experience in both ecosystems. That’s when patterns started to emerge—like how influencer tiers work completely differently, how trust metrics vary by market, and how ROI calculations need serious adjustments.
I’m curious: when you’re analyzing influencer campaign results across different markets, how do you handle the comparison problem? Do you normalize the metrics, or do you keep them separate and just interpret them differently? And more importantly—how do you convince your stakeholders that “success” actually looks different depending on where the campaign ran?
This is exactly the problem I see constantly. The normalization approach is necessary, but I’d push back slightly on one thing—before you normalize, you need to understand what’s driving the differences in the first place.
In my analysis work, I’ve found that it’s not just about engagement rates. It’s about several layers:
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Platform saturation: US Instagram is oversaturated with influencer content. Russia still has VK and Telegram as major players, which change the dynamics completely.
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Audience expectations: A US audience expects to see ROI language (“shop now”, direct links, urgency). Russian audiences respond differently to more subtle recommendation approaches.
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Sample size: This is critical. If you ran 3 influencer campaigns in the US and 15 in Russia, your confidence intervals are completely different. You can’t fairly compare them without accounting for variance.
What I do: I track engagement, reach, click-through, conversion, and CAC separately for each market. Then I calculate a market-adjusted efficiency score that accounts for platform differences and audience size. It’s not perfect, but it gives you an apples-to-apples comparison.
Also—and I say this from experience—don’t forget attribution. Influencer campaigns have a long tail of impact. Someone might not buy immediately after seeing an influencer post, but it builds brand awareness that contributes to purchases later. Your Russian market might show this differently than your US market.
We went through this exact pain point last year. My takeaway: stop trying to make the metrics identical. They won’t be, and they shouldn’t be.
What actually worked for us was setting market-specific success criteria up front. In Russia, we optimized for brand awareness and community engagement. In Europe (our expansion market), we optimized for conversion and CAC. Same influencers sometimes, completely different KPIs.
The comparison challenge is real, but I found it’s less about the mathematical normalization and more about understanding what business outcome you’re actually trying to achieve in each market. Are you trying to build brand recognition? Drive direct sales? Create community? That answer changes everything about how you interpret the data.
One specific thing: create a shared dashboard with colleagues from both markets. Sit down together and interpret the numbers. You’ll notice that someone in Russia reads the data completely differently than someone in the US—and both perspectives are usually right. That’s when you start to see the real insights.
I love this question because it’s forcing someone to think systematically about partnership value, which honestly most people skip.
One thing I’d add beyond the metrics discussion: get to know the influencers themselves across markets. I’ve noticed that Russian influencers and US micro-influencers have completely different working styles and expectations. A Russian influencer might be comfortable with detailed brand guidelines and longer-term relationships. A US creator might want more creative freedom and project-based work.
When you understand how they work, you understand better why the campaign results look different. It’s not always the data—it’s the execution approach.
I’d be curious to hear: are you working with the same influencers across both markets, or different ones? That completely changes how you should interpret the results.
From a creator’s perspective, I can tell you that the way a US brand briefs a campaign is usually very different from how a Russian brand does it. US brands tend to be more hands-off (“just make good content”), while Russian brands are often much more prescriptive.
That affects the quality of what gets produced, which then affects your metrics. So when you’re analyzing the numbers, remember that the content itself might be fundamentally different in terms of authenticity and polish, which impacts engagement differently.
Also—followers don’t mean anything. A Russian influencer with 50K followers might have more real engagement than a US influencer with 500K who has a lot of bot followers. Have you looked at audience quality, or just the raw metrics?
This is a classic attribution problem combined with market-specific baseline issues. Here’s how I’d approach it:
First, establish a control group in each market. Run parallel campaigns with identical budgets and similar audience sizes. This gives you a true performance baseline that accounts for market differences.
Second, use a standardized scorecard that weighs metrics by business impact. For example: conversion might be 40% of your score, reach might be 30%, engagement 20%, brand lift 10%. Adjust the weights by market based on your actual business objectives.
Third—and this is important—don’t try to make a single “winner” across markets. Instead, identify what works best within each market, then look for patterns. You might find that a certain influencer type outperforms consistently, or that a specific content format sees lower CAC, regardless of market.
The real comparative analysis comes from asking: “What’s the efficiency frontier in each market, and where are our campaigns relative to that frontier?” That’s what matters.
I work with a lot of brands scaling across regions, and honestly, the biggest mistake is overthinking this. Here’s what actually works:
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Define your benchmark first. What’s industry standard for influencer campaigns in each market? Use that as your comparison baseline, not some arbitrary internal target.
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Track the same core metrics everywhere: engagement rate, CTR, CAC, and LTV. Everything else is supplementary.
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Most importantly: don’t compare absolute numbers. Compare relative performance. A 2% engagement rate in the US might be 60th percentile for that platform. A 5% engagement rate in Russia might be 45th percentile. The second one is actually underperforming.
When you frame it this way—percentile ranking relative to market benchmarks—suddenly the comparison makes sense. And the strategic conversations become about incremental improvement within each market, not trying to force identical performance across different contexts.
Do you have industry benchmarks for your specific categories and markets? That’s where I’d start.