I’ve been wrestling with this for a while now. We work with influencers across Russian and US markets, and brand safety standards are all over the place. One influencer passes in Moscow but raises red flags in New York, and vice versa.
What I realized is that I can’t just throw an AI tool at this and call it done. I started building a workflow where we use automated signals—engagement patterns, audience demographics, posting consistency—but then actual humans with regional expertise review those flags. A Russian PR specialist catches nuance in audience composition that an algorithm might miss. Same with our US team.
The bilingual aspect is critical here. When we’re vetting creators, we’re not just looking at metrics. We’re looking at how they communicate with their audience, the tone of their captions, their history with brand partnerships. That takes someone who actually understands both markets.
I’m curious—are you automating the initial screening stage and then escalating to human review, or are you doing something completely different? And how do you decide which signals actually matter for your specific brand?
This resonates with me. We looked at 200+ influencers across both markets last quarter and tracked which ones actually delivered ROI vs. which ones just looked good on paper. The data was eye-opening—follower count did almost nothing to predict campaign performance. What mattered was engagement quality, audience overlap with our target demographic, and consistency in posting schedule.
We built a simple scoring system: 40% on audience quality (using third-party tools to verify), 30% on engagement patterns, 20% on brand alignment (manual review), and 10% on historical performance. The caveat is that this only works if you’re tracking actual results from past campaigns. Without that baseline, you’re just guessing.
For the bilingual angle, we found that Russian influencers often have very different audience expectations than US-based creators. Russian audiences value authenticity and long-form storytelling; US audiences respond more to quick, snappy content. So the vetting criteria have to shift based on market context.
One more thing—we’re using a tiered approach now. Tier 1 is automated flags: bot-like engagement spikes, sudden follower drops, suspicious audience demographics. Tier 2 is regional expert review of the flagged accounts. Tier 3 is brand alignment deep dive with our creative team. This has cut our vetting time by 60% while actually improving our partner quality. The key was being ruthless about which creators we escalate to Tier 3—we’re probably only approving 15-20% of initial candidates, but those are the ones who actually perform.
I love this conversation! You’re touching on something I see all the time—the tension between speed and safety. In my world, helping brands and creators connect, I see both sides getting frustrated.
Brands want fast approval because campaigns are time-sensitive. Creators want respect for their work and not to be treated like a liability. The vetting workflow you’re describing actually helps both. If a creator is legitimate, transparent vetting builds trust. If there are red flags, catching them early protects everyone.
I think the bilingual piece is huge for relationship-building too. When a brand’s partner manager speaks the creator’s language and understands their market context, the whole collaboration improves. It’s not just about fraud detection—it’s about building real partnerships. That’s where the magic happens.