I’m at the point where I’m second-guessing every influencer investment we make across markets. We’ll run a campaign in Russia, get some engagement numbers, then run something in the US, get different numbers, and I genuinely can’t tell if we’re comparing good decisions or just looking at apples and oranges.
The worst part is that our CFO keeps asking me to justify spend, and I can show metrics, but I can’t confidently connect them to actual revenue in a way that makes sense when you layer in the fact that we’re operating in two completely different markets with completely different customer behavior.
I’ve been trying to build benchmarks on my own—looking at historical data, trying to find patterns—but I’m realizing I don’t have enough comparable data to do this well. And the US team and Russia team aren’t always aligned on how they measure things, so even when I try to compare, I’m comparing apples to oranges.
I know other people are dealing with this exact problem. How are you actually doing it? Are you benchmarking against other brands? Getting help from external analytics experts? Or are you just accepting that cross-market ROI is a guessing game with better presentation?
I need to know what actually works because I’ve got Q2 budgets to allocated and I can’t keep operating on faith and assumptions.
Stop trying to compare campaigns directly. That’s your first mistake, and I made it too.
What you actually need is a two-step process:
Step 1: Build a reliable ROI model within each market. Don’t try to make them identical. In Russia, if your influencer campaign drove 2,000 visits and 60 purchases, that’s your baseline ROI for that creator size and category. In the US, maybe it’s 3,000 visits and 110 purchases. Those are different, and that’s okay.
Step 2: Once you have benchmarks within each market, you can then look at performance relative to those benchmarks. If a campaign is 20% above your Russian baseline and another is 25% above your US baseline, now you’re comparing apples to apples—both are “outperformers.”
The problem people run into is they try to build one global benchmark, and it doesn’t work because the customer behavior is too different.
For the CFO conversation: build three portfolios. Show historical performance of 10-15 campaigns in Russia, 10-15 campaigns in US, and then show how new campaigns are tracking against their respective benchmarks. That’s defensible. That’s not a guess.
How many campaigns have you actually run in each market that you can pull data from?
One more thing because this is important: you need to separate attribution from influence. Not every purchase that happens after someone clicks from an influencer post is actually ROI from the influencer. Some of those people would have found you anyway.
I use incrementality testing for high-spend campaigns. Same creative, same influencer pool, but one audience sees the post and one doesn’t (through geo or holdout). The difference in conversion between the two groups is your true ROI. It’s more work, but for 20%+ of your budget, it’s worth it.
Then for lower-spend campaigns, I use econometric modeling to infer the incrementality based on historical patterns. Rough, but better than nothing.
You can’t compare cross-market ROI until you’re measuring true ROI, not just correlation.
Анна’s framework is solid. I’ll add this: the reason you’re struggling is that most influencer ROI measurement is built on the assumption of a clean, single-source attribution. But with brands operating across markets, that assumption breaks.
Here’s how I think about it at a higher level:
Influencer campaigns are doing two things simultaneously:
- Direct response (trackable clicks → conversions)
- Brand lift (awareness, perception shift, competitive positioning)
You’re probably only measuring #1. That’s why cross-market comparison feels broken. A campaign that performs okay on direct response might be crushing it on brand lift, and vice versa.
If you’re serious about this, you need to measure both. That means:
- For direct response: attribution, incrementality testing, cohort analysis (what Анна described)
- For brand lift: lift studies, survey data, comparative analysis against competitors
Then when you compare cross-market, you’re looking at: “Russia campaign: 12% direct ROI, +8% brand lift. US campaign: 18% direct ROI, +3% brand lift.” Now you can actually talk about total business impact.
This requires more sophistication, but it’s honest. Most brands aren’t doing this, which is why they can’t justify influencer spend confidently.
Real talk: most of the time when agencies claim they have “proven ROI models” across markets, they’re either lying or they’re comparing things that aren’t comparable.
What I actually do for clients: I bring in external analysts who have worked across both markets. Not geeks in my team—actual people who’ve built businesses in both regions. They look at the data, validate methodology, and help us identify blind spots. It’s expensive, but it saves us from making terrible allocation decisions later.
Second thing: I use benchmarking consortiums. There are groups of non-competing brands that share anonymized campaign data. Not perfect, but it gives you a sense check against reality instead of just your own historical data.
Third: I compartmentalize. I’ll run 60% of budget on proven tactics (based on historical ROI in each market), 30% on optimized campaigns (testing small variations), and 10% on pure learning (new creators, new platforms). That structure acknowledges what we know vs. what we’re testing.
For your CFO: pitch it as a portfolio approach, not a single campaign ROI. That’s way more defensible and more realistic.
I love that you’re thinking about this rigorously because it affects partnerships. When brands actually understand their ROI, they brief creators better, they’re more realistic about expectations, and deals close faster.
From a relationship side: once you have your benchmarking sorted, share it with influencer partners in both markets. “We know that creators at your tier in Russia typically drive X ROI, and in the US typically drive Y.” Transparency actually increases trust and helps creators set their own pricing accordingly.
Also, creators in each market often have their own sense of what works and what doesn’t. Tap into that. They see performance across brands, and their intuition about ROI patterns is actually valuable data.
Just a creator perspective: I can tell when a brand doesn’t understand their own ROI because they brief me vaguely or they keep changing metrics mid-campaign. When you figure out what you’re actually measuring, communicate it clearly from the start.
Also, some of us creators know our ROI better than the brand does because we track our own links and see what converts. If you ask, we can probably tell you what realistic expectations look like in our market. We want you to be successful too—that’s how we get hired again.