I’ve been running campaigns for a DTC brand that has audiences in both Russia and the US, and honestly, comparing results between the two markets is driving me crazy. The metrics just don’t translate cleanly.
Like, I’ll run a campaign with a Russian-speaking creator that generates 15% engagement rate, and then a similar campaign with a US creator gets 6% engagement. But the ROI is higher on the US side because the conversion rate is better, even though engagement is lower. How do I even compare that?
I’ve tried basic metrics—reach, engagement, conversions—but they behave so differently across markets that I can’t tell if I’m optimizing campaigns well or just lucky. Attribution is messy too. US customers might see an Instagram post and convert a week later. Russian audiences often buy immediately or not at all.
I’m also noticing that engagement rates mean different things. A high comment rate in the Russian market might indicate community, but in the US it could just be algorithm gaming. Conversion behavior is totally different too.
Right now I’m just tracking everything separately and praying I’m not missing patterns. Has anyone actually solved this? How do you measure influencer ROI when you’re bridging two completely different market behaviors?
Okay, this is my wheelhouse. The key insight is that you cannot use the same metrics to compare performance across markets—you need market-specific benchmarks.
Here’s how I approach it: First, establish separate baseline benchmarks for each market. Run your own internal historical data analysis. What’s the average engagement rate for your Russian audience on creator content? What’s the average for your US audience? Document these as your baselines.
Second, stop comparing engagement rates directly. Instead, compare conversion efficiency per engagement point. So if Russian content has 15% engagement and 3% conversion, that’s 0.2% conversion per 1% engagement. US content with 6% engagement and 8% conversion is 1.33% conversion per 1% engagement. Now you can actually compare quality.
Third, track LTV-adjusted ROI, not just immediate conversion. Russian audiences might convert immediately, but what’s their lifetime value? US audiences might convert slower but spend more over time. That changes everything.
I also recommend tracking time-to-conversion as a separate metric. How long between content view and purchase? That behavioral difference is crucial for attribution and optimization.
One more thing: implement UTM parameters that are specific to each market. Not just utm_source=instagram, but utm_source=instagram_ru or utm_source=instagram_us. This lets you track cross-platform behavior and understand if US customers are seeing Russian content and vice versa. That data is gold for understanding how your audiences actually move.
Yeah, we’ve hit this exact issue expanding to Europe. The metrics game is brutal when you cross markets.
For us, the breakthrough was stopping trying to compare and just optimizing within each market. We set separate ROI targets for each region based on local benchmarks. Russian market: target 2.5x ROAS. European market: 3.5x ROAS. Both are measured against their own baseline, not against each other.
Also—and this might sound obvious but it wasn’t obvious to us—we adjusted our creator brief based on market behavior. For Russian audiences, we brief creators for immediate, direct CTA. For US audiences, we brief for narrative and storytelling, because the buyer journey is longer.
The real insight: your creator isn’t broken. Your measurement framework is missing the nuance. Once we separated our approaches, optimization became way easier.
From an agency perspective, we handle this by implementing a dashboard that separates metrics by market tier, not by campaign.
Here’s our structure: We track core metrics (reach, engagement, conversions) separately for each market. But then we tie those to brand health metrics that are constant across markets—like brand awareness lift, top-of-funnel metrics, mid-funnel, bottom-funnel.
What we’ve found: engagement metrics are market-dependent and noisy. But if you track the actual funnel movement—how many impressions move to click, how many clicks move to conversion—you get a clean picture that IS comparable across markets.
So my recommendation: build a conversion funnel model for each market, then compare funnel efficiency, not vanity metrics. That’s where the real signal is.
Also, consider segmenting by audience source. Track separate metrics for: (1) existing customers seeing new creator content, (2) new audiences from creator reach, (3) retargeted audiences. Behavior is wildly different across these groups and markets amplify those differences.
Honestly, from my side as a creator, I think you’re overthinking this a bit. Here’s what I’ve noticed: my Russian followers engage way faster and buy quick, but they’re also quick to lose interest. My US audience takes longer to engage but they’re more loyal.
So maybe instead of comparing metrics directly, you should think about what you’re actually optimized for: quick revenue (Russian market), or long-term customer value (US market). Those are different goals, so different metrics matter.
When I’m briefed for a Russian campaign, I lean into urgency and quick CTA. For US audiences, I focus on building narrative. The ROI is similar but through different mechanics. So yeah, the metrics “breaking” might just be because you’re trying to apply the same success criteria to different customer behaviors.
Data-driven take: you need to implement cohort analysis separated by market and audience source.
Track this: For content from [Creator Name], Russian-speaking audience, what’s the acquisition cost, order value, and retained customer rate at 30/60/90 days? Then run the same analysis for US-speaking audience. US content, Russian audience. US content, US audience.
Once you have that matrix, you can actually see which combinations work and which don’t. You might find that US creators are terrible at reaching Russian audiences but amazing at US audiences, and vice versa. That’s actionable intelligence.
Also, implement proper attribution modeling. First-click, last-click, and linear models all tell different stories. For international campaigns with longer buyer journeys, you probably need time-decay attribution where recent touchpoints (like creator content) are weighted more heavily.
My final recommendation: stop trying to optimize cross-market in aggregate. Instead, optimize within market, then compare market-to-market performance once each is individually optimized. That’s when you’ll get real clarity.
One tactical thing: implement a cross-market performance scorecard. Track ROI, CAC, LTV, and retention rate for each market. Update it monthly. That simple dashboard will show you where your optimization efforts should actually focus.