I’ve been thinking about this for a while now. We recently tried to document a success story for one of our clients—a Russian beauty brand that’s been making real traction in the US market. The challenge? We needed to tell the story in a way that made sense to both our Moscow stakeholders and our partners in New York.
The problem I kept running into was that what “success” looked like varied wildly between markets. In Russia, we were tracking engagement rates and brand sentiment. In the US, everyone wanted to see conversion rates and customer acquisition cost. Same campaign, totally different metrics.
So here’s what we ended up doing: we structured the case study around three core sections—objectives (what we were actually trying to solve, framed for both markets), actions (the specific tactics we deployed, with cultural context), and results (the metrics that mattered to each audience, presented side-by-side).
The “actions” section was where it got interesting. We didn’t just list what we did. We explained why certain approaches worked differently across regions. For example, influencer selection criteria in Russia prioritized audience loyalty and niche authority, while US partners cared more about audience demographics and cross-platform reach. By laying out both perspectives, the case study became a teaching tool instead of just a trophy.
What surprised me most? The US team actually learned something from understanding the Russian approach. They realized they’d been over-indexing on follower count and missing micro-influencers with genuine community trust.
For anyone building these kinds of cross-market case studies: don’t try to force one narrative. Instead, show how the same objectives led to different actions in different contexts, and let the results speak for themselves in the language of each market.
Has anyone else found a format that actually works for bilingual stakeholders? I’m curious if there are patterns I’m missing.
Mark, это именно то, что нужно больше людям! Я часто помогаю брендам и инфлюенсерам выстраивать партнерства между странами, и одна из главных боль—что никто не говорит на одном языке про успех.
Я обожаю твой подход с таблицей «задачи → действия → результаты» для каждого рынка. Это кажется очень логичным. Я уже видела, как провалам именно потому, что бренд описывал успех по-русски (вот смотрите, охват вырос!), а американский партнер хотел видеть ROI на каждый доллар. Они говорили про разные вещи.
У меня вопрос: когда ты писал этот кейс, ты консультировался с обеими командами сразу, или сначала собрал от них данные, а потом переработал? Я думаю, что процесс может быть такой же важной частью, как сам результат.
Отличный разбор. Вот что мне нравится в твоем подходе: ты не пытался навязать единые метрики, а признал, что они изначально разные.
Но у меня есть конкретный вопрос к цифрам. Ты упомянул customer acquisition cost для US и engagement rate для Russia. Как выглядели абсолютные цифры? Например:
- CAC в US: $X на одного клиента
- Engagement rate в Russia: Y%
- Средний заказ: $Z
- Retention через 3 месяца: W%
Мне кажется, что даже если метрики разные, должны быть какие-то универсальные показатели, которые позволяют сравнить эффективность одной стратегии над другой. Как ты к этому подошел?
Mark, спасибо за такой практичный пример. Мы сейчас готовим выход нашего продукта в Европу, и я как раз столкнулся с этой проблемой: инвесторы в России смотрят на одни метрики, европейские партнеры—на совсем другие.
Твой подход с фреймом задачи–действия–результаты кажется очень применимым. Я хотел бы понять: насколько подробным ты делал разбор действий? Типа, ты писал:
- Действие 1: выбрали 15 микро-инфлюенсеров в Russia на основе X критериев
- Действие 1 (US): выбрали 30 микро-инфлюенсеров на основе Y критериев
Или ты показывал эти действия в одной колонке, но с пояснениями, почему они отличались? Я думаю, что вторая версия приносит больше ценности тому, кто читает кейс впервые и ничего про рынки не знает.
This is solid thinking, Mark. I’ve run into the exact same wall when pitching case studies to both Russian and US clients. They literally have different definitions of what “successful” means.
Here’s what I noticed in your structure: you’re essentially creating a bilingual brief that functions as both a case study and a strategy document. That’s actually valuable IP. A lot of agencies—myself included—struggle to package this kind of cross-market work in a way that can be replicated.
Two thoughts: (1) Did you create separate decks for each market, or did you build one master document with the side-by-side comparison? (2) How did this structure perform when you tried to pitch it to new clients? Did the cross-market context actually help them understand what the agency was capable of, or did they tune out because it felt too complex?
I’m asking because I’m thinking about building something similar for our portfolio.
This is really helpful to see from the strategic side! As a creator working with brands in both markets, I can tell you that feeling of “we’re celebrating different things” is SO real.
I had a campaign where the Russian brand was obsessed with video views and shares (they kept saying “Look at the engagement!”), and the US brand kept asking about actual sales. They literally didn’t believe I was being effective until they saw the purchase link clicks. Same content, same audience (mostly), completely different definitions of success.
I love how you framed it as a teaching tool for both sides. That’s actually the most useful thing, because it means next time I talk to a new brand, I can point to something like this and say “Here’s how we measure it across different markets.” Less drama, more clarity.
Did you share this format with creators and influencers too, or was it mainly for internal stakeholder alignment?
I appreciate the detailed walkthrough. This is exactly the kind of rigor we need more of in cross-market work.
One layer I’d add: beyond just presenting different metrics, there’s value in identifying which metrics actually drive the others. For instance, if your Russian engagement rate of X% correlated with a US conversion rate of Y%, that becomes predictive. It means for the next campaign, you know that when you see the engagement metric hit Z in Russia, you can forecast the US outcome with reasonable confidence.
I suspect what you’re really building here isn’t just a case study—it’s a model that makes future planning more accurate. Did your analysis go that deep, or was it more about transparent reporting? The reason I ask is that if you’ve cracked the correlation piece, that’s genuinely proprietary and worth documenting as methodology.