This has been bugging me for a while, so I’m throwing it out to the community.
I’ve got campaigns running in multiple regions, and I’m trying to do apples-to-apples comparisons of engagement, CAC, and ROAS. But every region seems to have its own quirks, and I’m not always confident I’m measuring things the same way.
For engagement, is it comments+likes+shares? Does video watch time count? Does it vary by platform? By region?
For CAC, am I accounting for differences in average order value by region? Currency fluctuations? Different cost structures?
For ROAS, how do I reconcile the fact that customer LTV might be wildly different across regions?
I feel like I’m inventing new definitions every time I run a new campaign, and I end up with metrics that look good on paper but don’t actually help me make decisions. I want to be able to look at a campaign in region A and a campaign in region B and know, with confidence, which one actually performed better.
How do you standardize these metrics so they’re actually comparable? And more importantly, how do you make sense of what the numbers are telling you? Do you have documentation or case studies from campaigns where someone clearly laid out their measurement framework?
Standardization is the foundation of everything. Here’s exactly how I do it:
Engagement: We define it as (comments + likes + shares + saves) / reach. We exclude clicks to links because that’s a different metric (click-through rate). We use the same definition across all platforms, and we measure it 7 days post-publication. Why 7 days? Because that’s where the pattern stabilizes. After that, additional engagement is noise.
CAC: This one’s tricky across regions. Here’s our formula: (Total Campaign Spend) / (New Customers Acquired) * (Blended LTV Index). The blended LTV index accounts for regional differences. So if US customers have 3x LTV compared to Russian customers, we normalize that into the CAC calculation. Now a $15 CAC from Russia might actually be equivalent to a $45 CAC in the US in terms of long-term value.
ROAS: (Revenue from Campaign) / (Total Campaign Spend). But here’s the key: We measure it consistently at 30, 60, and 90 days. Different regions have different sales cycle lengths, so reporting at a single time point is useless. We track the entire curve.
The real game-changer: I maintain a benchmark database of similar campaigns (same product category, similar audience size, similar influencer tier) across regions. At the end of each campaign, I compare our results to that benchmark and ask: Is this aligned with what we’ve seen before, or is something different?
What’s your current measurement window for ROAS?
You’re asking exactly the right question, but the answer isn’t about the metrics themselves—it’s about having a framework that everyone agrees to.
Here’s what I’ve learned from running campaigns at scale: Standardization only works when you have three things:
- Agreed-upon definitions (which you’re trying to create)
- Documented precedent (case studies from past campaigns using the same framework)
- Regular calibration (comparing your results to those precedents to catch drift)
For engagement, we use: total interactions / average followers, measured at days 1, 3, 7. Platform differences matter, so we track them separately but report a blended score.
For CAC: (Media Spend + Influencer Fees) / New Customers. We don’t adjust for LTV initially—we track CAC separately from CAC-to-LTV ratios, because mixing them obscures what’s actually driving efficiency.
For ROAS: (Revenue from Campaign - COGs) / (Total Spend). We measure at 14, 30, 60, and 90 days. Why multiple windows? Because you need to see the shape of the curve. A high ROAS at day 14 with a cliff drop at day 30 tells a different story than steady growth.
But here’s what I can’t stress enough: You need a case library. Not theoretical best practices—actual campaigns you’ve run or observed, with documented results and the thinking behind them. When your next campaign is running and the numbers look weird, you reference a comparable case and ask: Is this pattern normal or an anomaly?
Do you have that infrastructure built out?
I’ve been where you are, and it’s maddening because the metrics themselves aren’t that complicated—it’s reconciling them across regions that’s painful.
When we started expanding, we had the same problem. We’d run a campaign in Russia, get a certain ROAS, then run what looked like the same campaign in the US and get a completely different number. Were we better at influencer selection in one market? Was the product a better fit? Or were we just measuring differently?
What helped: We brought in someone who’d done this before—someone who’d worked across markets and had a system. They helped us standardize, and suddenly the numbers started making sense.
The real value was seeing real examples. “Here’s a campaign we ran in Russia. Here’s a similar one in the US. Here’s why the metrics look different. Here’s what we learned.”
I think what you actually need is access to that kind of thinking—working examples, not just templates. Do you have that available?
Standardized metrics are competitive advantage. Here’s our system:
We use a scorecard approach:
- Engagement Score (0-100): Blends reach, engagement rate, and sentiment. Same calculation across all regions.
- Efficiency Score (0-100): CAC vs. benchmark, ROAS vs. historical average. This is normalized by region.
- Growth Score (0-100): Customer acquisition velocity, retention indicators, repeat purchase rate.
Each score has clearly defined inputs and calculations. No ambiguity.
But the scorecard alone isn’t enough. We pair it with a case archive—every significant campaign we run is documented with scorecards, learnings, and decision-making rationale. When a new campaign is in progress, we reference similar cases and ask: Are we tracking ahead or behind? Why?
That’s how you move from “metrics that look good” to “metrics that inform decisions.”
Do you have a standardized scorecard like that, or are you still working campaign-by-campaign?
I love that you’re thinking about this systematically! This is exactly the kind of conversation that brings people together.
One thing I’d add: The people who’ve solved this problem usually love sharing their frameworks. It’s not proprietary—it’s just good practice. And conversations with those people are gold.
There are definitely folks in this community who have solid standardized metrics across regions. Would it help to connect with someone who’s already cracked this code? Sometimes a 20-minute conversation beats weeks of trial and error.
I could facilitate some introductions if you’re interested!
From a creator perspective, I notice that engagement metrics vary wildly by platform and region. Like, a video that gets 10K views and 500 comments in one market might get 10K views and 200 comments in another, and the brands always seem surprised by that.
What would be helpful for me—and I think for brands too—is if there were clear case examples of campaigns that showed: “Here’s what engagement looked like, here’s how we measured it, here’s what it actually meant for results.”
That way, when a brand briefs me on engagement targets, I’d understand if their expectations are realistic for that market.
Do you have that kind of reference material available?