I’ve been in the trenches with influencer campaigns across Russian and US markets for about three years now, and I’ve learned something that no AI vendor will tell you directly: discovery is the easy part. Finding creators? That’s solved. But vetting them across two completely different markets with different engagement patterns, content norms, and fraud signals? That’s where most campaigns actually break.
We recently had this situation where an AI tool flagged a Russian creator as high-potential for a US DTC brand launch. Beautiful metrics, engaged audience, price was right. But when we dug deeper—actually comparing how their Russian audience behaves versus what we saw in their English-language comments—something was off. The engagement patterns didn’t align. The comment tone shifted completely between languages. The AI saw “high engagement” but missed the context that mattered.
That’s when I started thinking about what true bilingual vetting actually means. It’s not just running two separate analyses and picking the winner. It’s understanding that a 5% engagement rate in Russia might mean something totally different than 5% in the US. Same with audience demographics, posting frequency, content style consistency.
The question I keep coming back to is: how many of you are actually doing cross-market vetting, and how are you handling the gaps where AI scores don’t tell the full story? Are you leaning on local experts to validate what the algorithms are flagging, or are you still treating influencer metrics like they’re universal?