We’re about to run our first coordinated influencer and UGC campaigns in both the Russian and US markets simultaneously, and I’m realizing I don’t really know how to compare results fairly.
The benchmarks are completely different—cost per acquisition in the US is way higher, engagement rates are different, audience behavior is different. But I need to report to investors and my leadership team on ROI, and I’m worried that if I just look at raw numbers, I’ll either over-celebrate wins that are actually normal for the market or completely miss underperformance that looked fine on the surface.
I’ve been digging into analytics tools, but I’m getting overwhelmed with metrics. Impressions, reach, engagement rate, CTR, ROAS, CAC, LTV… how do you actually know which ones to track and report on? And how much do I need to adjust for market differences?
Also, I’m curious about benchmarks. Do you actually use benchmarks from US-based experts to inform your Russian campaigns, and vice versa? Or are the markets so different that comparing them is basically useless?
Have any of you actually built a dashboard or framework that lets you measure campaign success consistently across markets? What did you learn about what actually translates and what’s completely different?
This is such a smart question to ask early. I’ve seen so many brands get confused about performance because they’re comparing apples to oranges.
From my perspective working with creator partnerships, here’s what I’ve found: the metrics that actually matter for partnership health are different from the metrics that matter for campaign ROI. You need to track both.
For partnerships, I focus on:
- Creator response time and professionalism
- Content quality consistency
- Ability to adapt and iterate
- Willingness to promote across multiple channels
These are relationship metrics, not performance metrics, but they heavily influence campaign success.
For actual campaign measurement, my advice is to have a primary metric per market (not trying to compare them directly) and then track secondary metrics for learning.
Also, don’t underestimate the value of qualitative feedback from creators in each market. They see how audiences actually respond, not just what the numbers show. I always ask creators: “What worked? What didn’t? Why do you think that?” Those conversations often reveal issues that raw data misses.
I’d be really interested in seeing what dashboard you build. Happy to give feedback on whether it’s tracking the right things from a partnership perspective.
Okay, this is my domain, and I’m going to give you a framework that actually works.
First, stop trying to compare metrics directly across markets. The metrics you should track are:
Core Performance Metrics (per market):
- ROAS (Return on Ad Spend) - this is your primary metric
- CAC (Customer Acquisition Cost) - market-specific baseline
- Conversion rate - by traffic source
- Cost per engagement - normalized for market
- Time-to-conversion - when do people actually buy?
Secondary Learning Metrics:
- Engagement rate (likes, comments, shares)
- Click-through rate
- Video completion rate (if applicable)
- Audience sentiment (if you’re tracking it)
The Critical Part: Normalization
Don’t compare US CAC directly to Russian CAC. Instead:
- Calculate your baseline CAC for each market before running influencer campaigns
- Measure the reduction in CAC as a result of influencer campaigns
- Compare the percentage improvement, not the absolute numbers
Example: If your baseline digital CAC in US is $50 and influencer campaigns bring it to $45 (10% improvement) vs. Russia going from $8 to $7.50 (6.25% improvement), the US campaign is actually more efficient in that market’s context.
On Benchmarks:
I’ve analyzed hundreds of campaigns. Here’s what transfers:
- Engagement rate benchmarks are somewhat comparable (adjust by platform)
- CAC ratios are not directly comparable
- ROAS expectations are market-specific
What I’d recommend: build market-specific benchmarks for yourself based on your historical data, then use industry benchmarks only as sanity checks.
Dashboard Framework:
Campaign Performance (by market):
- Spend (total)
- Conversions (total)
- ROAS (spend ÷ revenue)
- CAC (spend ÷ conversions)
- Engagement rate (normalized)
- Creator performance tier
Variance Analysis:
- Actual ROAS vs. target ROAS
- Top 3 performing creators (by ROAS)
- Bottom 3 performing creators
- Recommendations for next cycle
I’ve got templates I use for this. Happy to share if you’re interested.
This is a huge pain point for us because I was exactly where you are—trying to compare metrics that don’t actually compare.
Here’s what we learned the hard way: benchmarks from US experts are useful, but you have to use them carefully. They can tell you if you’re in the ballpark, but they can’t be your primary guide.
We built a dashboard that tracks:
- Market-specific baseline (what we measured before influencer campaigns started)
- Campaign results (during influencer campaigns)
- Improvement percentage (not absolute comparison)
- Cost per each metric (for apples-to-apples comparison)
The biggest insight we had: US audiences have longer decision cycles. Our Russian campaigns might convert in 3-5 days, but US conversions took 10-15 days. This completely changed how we measured success—if we’d looked only at 7-day conversion data, we’d have thought the US campaign was failing.
For benchmarks, we did this:
- Got benchmarks from 2-3 US marketing experts in our space
- Compared them to our actual historical data
- Used the gap between expert benchmark and our performance to inform optimization
Example: Expert said engagement rate should be 3-5%, we were at 1.8%, so we optimized creator selection and content format.
One more thing: investor reporting is different from internal analysis. For investors, we showed:
- Overall ROAS by market
- Trend (improving or declining)
- Whether we hit targets
- Specific optimizations we made
We didn’t overload them with every metric. That’s internal data.
How are you planning to structure reporting? That might help me give more specific advice.
From an agency standpoint, I can tell you that most brands get this wrong initially, and it usually costs them.
Here’s what I recommend:
Step 1: Stop comparing metrics directly. Different markets, different baselines. Instead, measure efficiency within each market.
Step 2: Track these (per market):
- ROAS (everything else derives from this)
- CAC (for unit economics)
- Engagement rate (for content quality)
- Creator performance tier (who delivered, who didn’t)
Step 3: Build month-over-month improvement tracking. This tells you whether your optimization is working better than time-based expected improvement.
On benchmarks: US benchmarks are useful for sanity checking but not for goal-setting. Set your own goals based on your historical data and market research.
Pro tip: Don’t mix marketing metrics with partnership metrics. Separately track:
- Campaign performance (ROAS, CAC, etc.)
- Creator performance (professional, responsive, quality)
The best creators aren’t always the highest ROAS performers. Sometimes a mid-tier performer with great feedback and reliability is worth more.
Reporting cadence: Weekly internal tracking, monthly investor reporting. Don’t give them daily noise.
I’ve got a simple Google Sheets template that works for this. A lot of my clients use it to stay sane when managing cross-market campaigns.
As a creator, I don’t think about these metrics, but I know when a brand is making good decisions about them because they communicate way better.
Brands that measure carefully tend to:
- Give creators clear feedback on what worked
- Iterate quickly rather than limp along with underperforming content
- Recognize when something isn’t working and try a different approach
- Actually come back for more campaigns
I think from a creator’s side, what matters is: are you measuring individual creator performance? Because if I’m doing UGC for you, I want to know my engagement rate, my click rate, my conversion contribution. That tells me whether I should keep collaborating with you or whether I need to adjust my approach.
So when you’re building your dashboard, make sure it breaks down performance by creator, not just by market. That’s how you actually get better at selecting creators for future campaigns.
Strategic framework for this:
The Three-Tier Metric System:
Tier 1 (Primary—report this to investors):
- ROAS by market
- CAC vs. LTV ratio
- Campaign profitability
Tier 2 (Secondary—internal optimization):
- Engagement rate
- Click-through rate
- Conversion funnel by step
- Time-to-conversion
Tier 3 (Diagnostic—troubleshooting):
- Creator-level performance
- Content-type performance
- Audience segment performance
On Cross-Market Comparison:
Don’t. Instead, measure each market against its own historical baseline and against your predetermined targets.
On Benchmarks:
Use them as bounds checks, not targets. If US industry benchmarks say ROAS should be 2-4x and you’re at 1.5x, investigate. If you’re at 3.2x, you’re performing well. But don’t target exactly what the benchmark says.
Dashboard Architecture:
- Daily: campaign spend, conversions, ROAS trend
- Weekly: creator performance, content performance, optimization recommendations
- Monthly: market comparison (performance vs. target, not vs. each other), investor summary
One critical insight: Most brands underestimate how much platform and audience composition affects metrics. A 2% engagement rate on TikTok is completely different from a 2% rate on Instagram. Normalize for platform, then compare creators within platforms.
Build your dashboard iteratively. Start with ROAS and CAC, then add complexity as needed. Most teams track too many metrics and end up confused.