Influencer marketing should be measurable. Most of it isn't.

Marketing budgets get approved on forecasts. The CMO who tells the CFO "we'll spend $200K and see what happens" gets fired. So why has influencer marketing spent a decade pretending forecasts don't apply?

We forecast every campaign before it ships. Predicted CPA band, expected reach, conversion estimate. We're wrong sometimes — but we're wrong with numbers, which means we can adjust. Most agencies are wrong with vibes.

Impressions, reach, CPM — these are the comfort metrics agencies hide behind when conversions don't materialise. They'll always look good, because they're measuring the easy thing.

We track every campaign from first click through D60 retention. The number that matters is "did the visitor become a customer who stuck around" — not "how many eyeballs did we technically reach."

Most agencies pitch creators based on follower count, recency on the platform, or who they happen to have a relationship with. None of those things tell you whether the creator's audience actually overlaps with your customer profile.

We start with audience-product fit. InfluBase.io scores every creator-brand pairing on demographic overlap, content affinity and historical conversion behaviour. The shortlist you see is the result of filtering — not the result of "creators we know."

Most influencer agencies are creator-shop houses — they sign 10–50 exclusive creators at low rates, mark up to brands, and force every brief through that fixed roster. The economics drive the campaign: the agency's cash comes from the spread on exclusivity, not from whether the creator was right for your product. Your campaign comes second.

We've built the opposite model. Our edge is access to the entire creator market — 287M+ verified records across YouTube, TikTok, Instagram and Twitch, with zero exclusives. When a brief comes in, the AI scoring runs against the full pool and picks the creators with the highest probability of converting on your specific product. The right creator wins, regardless of whether we'd negotiated a discount on them.

An agency that runs 50 mobile-game campaigns a year learns more about mobile-game performance than one that runs 5. Specialisation is how you build the dataset that makes prediction possible.

We started in mobile gaming because that's where measurement was hardest and the lessons compounded fastest. The frameworks we built there now apply across 12 verticals — but the depth came from focus.

Every "influencer marketing platform" you've heard of is fundamentally a CRM with a creator search bar. Useful, but it doesn't know whether the creator will work for your specific product.

We built InfluBase.io as the prediction layer. It indexes 287M+ creators and learns from every campaign we deliver. The agency feeds the platform; the platform feeds the agency. Each one improves the other every quarter.

Treat creators like you'd treat a Facebook ad slot — fungible, low-touch, race-to-the-bottom on price — and you get the campaign you deserve: filler content from a creator who doesn't care if your product succeeds.

We pay creators on delivery, never on platform credit. We pick a smaller number of better matches and rebook them. The result: creators who actually want our briefs, who push back on bad ideas, and who deliver on the timeline they committed to.

The whole point of building a prediction model is so the customer can audit the prediction afterwards. Our forecast is on paper before we ship. Our delivery is on paper after we ship. The variance is the conversation.

If we missed, you know exactly where. If we hit, you know exactly why — and what to scale next. That's the only path to a marketing channel you can actually plan around.