I broke down my influencer campaign metrics by location and discovered I was measuring the wrong things—here's what I changed

Кейсы и истории успеха
1

I’m sharing this because it took me way too long to figure out, and I think others are probably doing the same thing unknowingly.

Last year I ran an influencer campaign that looked decent on paper: reasonable engagement rates, decent ROAS, solid conversion numbers. But when I tried to compare the Russia results to the US results, everything looked off. The metrics didn’t make sense side-by-side. Russia numbers looked weak compared to US, but when I dug in, it wasn’t actually that simple.

Turns out I was comparing things that weren’t comparable. I was looking at standard US e-commerce benchmarks (30% CTR is low, 5% conversion is average, etc.) and applying those to Russian market data. But Russian platforms have different infrastructure, different audience behavior, different creator economics. A 3% CTR on VK is actually strong. A 2% conversion in Russia might be better than 4% in the US depending on product and market maturity.

I also realized I was mixing metrics that didn’t belong together. I’d measure engagement rate on Instagram US content but cost-per-acquisition on Russian TikTok. Different platforms, different currencies, different customer lifecycles. I was basically comparing inches to kilograms.

Here’s what changed:

First, I stopped using US benchmarks as the baseline. I researched actual Russian market benchmarks for each platform. Turns out there are reports on this (took time to find, but they exist).

Second, I standardized my measurement approach: Same platforms → same audience segment → consistent KPIs. If I’m measuring engagement on Instagram US, I measure engagement on Instagram Russia, not mixing in TikTok.

Third, I started looking at relative performance (percentage change from baseline) instead of absolute numbers. That let me actually compare growth trajectory across regions, even if the starting points were different.

Most importantly, I shifted from “does this metric look good?” to “does this metric tell me something actionable about optimization?” A 15% engagement drop in one region might be a red flag in another, depending on context.

Now when I write up campaign results, I lead with what the metrics actually tell us about creator performance and audience behavior—not just whether numbers crossed an arbitrary threshold.

How are you currently benchmarking influencer performance when you’re operating across multiple regions? Are you using region-specific standards, or are you still comparing everything to a single set of metrics?

2

Ты описал ровно ту проблему, которую я видела в десятке кейсов. Это классический случай, когда люди путают “метрика показывает хороший результат” с “метрика показывает хороший результат для этого рынка”.

Твой момент про VK CTR vs Instagram—это именно то. Я делаю обычно так: собираю 6-месячные данные для каждого рынка по каждой платформе отдельно, вычисляю 50-й перцентиль (не среднее, а медиану—она устойчивее к выбросам), вот это становится моим локальным бенчмарком. Потом я смотрю: мой инфлюенсер выше или ниже медианы?

Вещь, которую ты мог упустить: сезонность. В России и США разные праздники, разная школьная синхронизация (это влияет на покупки), разная экономическая цикличность. Когда я сравниваю май в США с маем в России, это уже не совсем честное сравнение. Ты это учитывал?

3

Вторая вещь—ROAS. Ты упомянул ROAS, и это хорошо, потому что это кросс-рыночная метрика. Но даже здесь есть ловушка: если ты не стандартизировал атрибуцию (когда ты считаешь, что привели инфлюенсеры), то ROAS может быть не сравним. В США много людей используют first-click аппроуч, в России часто last-touch. Твоя методология шла на это?

4

Кстати, вот конкретный вопрос: когда ты собирал данные по инфлюенсеру, ты смотрел на его аудиторию? Типа, follower growth rate, engagement of followers vs fake accounts, age distribution? Потому что инфлюенсер может показать 15% engagement в России, но если половина основания—фейки, то это не 15%. Я бы хотел узнать, как ты верифицировал качество перед сравнением.

5

Я подхожу к этому с другой стороны—с точки зрения партнёрства с инфлюенсерами. Но я вижу то же самое: когда я рекомендую инфлюенсера в России, я смотрю на одни метрики, когда рекомендую в США—на совершенно другие. И это вообще не потому, что я менее компетентна. Просто экосистемы разные.

Вещь, которая мне помогает: я спрашиваю инфлюенсеров не просто “какой у тебя engagement”, а “какова твоя история с брендами вроде X?” Отпечаток опыта—вот что реально важно. Инфлюенсер, который не делал кампаний в нише fashion, не будет хорошо работать в fashion, независимо от того, что скажут цифры.

Твой подход к стандартизации—это правильное направление. Я бы добавила: разговаривай с инфлюенсерами, узнай реальные истории. Метрики врут, но люди обычно нет.

6

You’ve identified something that agencies deal with constantly but don’t always articulate well. When I’m managing multi-market campaigns, the metric standardization issue is probably 30% of the management overhead.

Here’s the added layer: client expectations. A US client expects to see ROAS, CAC, payback period—they speak fluent unit economics. A Russian client might be more interested in brand awareness lift, share of voice, or “did we beat competitor X’s engagement?” Same campaign, different reporting. That’s not you screwing up; that’s market-driven.

One thing I’d push on: attribution modeling. You mentioned cost-per-acquisition, but did you standardize the customer journey? In the US, we often see shorter funnels (see → click → buy), but in Russia, there’s often more social-y middle ground (see → engage → save → buy later). If you’re measuring CPA at the click level versus the purchase level, you’re looking at different things.

How granular did you get with funnel analysis versus just top-line metrics?

7

Reading this as a creator who’s worked with brands across markets, I’m like YES to all of this. Because on my end, I’ll get a DM that says “your engagement is low compared to other creators” and I’m like… compared to where? My US followers engage differently than my Russia followers, and not because I’m doing anything wrong.

Also the fake accounts thing is HUGE. I’ve seen creators get penalized for “low engagement” when it turned out half their followers on one platform were bots. That’s not a creator problem, that’s an audit problem.

One thing I’d add: growth rate matters too. An influencer with 10k followers gaining 2% per month is stronger than one with 50k followers gaining 0.3%—but you’d miss that if you’re just looking at absolute numbers.

8

This is solid foundational work. You’ve essentially built a normalization framework, which is the prerequisite for any serious comparative analysis across markets. Most teams skip this step and wonder why their data doesn’t make sense.

Three structural questions:

  1. Segmentation depth: When you standardized metrics, did you segment by creator tier (mega vs macro vs micro)? Performance characteristics are wildly different, and mixing them skews your baseline.

  2. Causal vs. correlation: You’re measuring performance, but are you isolating what caused differences? If Russia outs-performs on engagement but underperforms on conversion, is that content quality, audience purchasing power, or something else? That distinction changes strategy.

  3. Forward-looking protocol: Did you build this into a repeatable measurement framework for future campaigns, or was it a one-time analysis? Because if you can’t maintain consistency, benchmarks become useless.

How did you document and operationalize this so your team can actually use it going forward?