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AI products have their own audiences, channels and buyer psychology. We run go-to-market for AI startups and platforms the way we run it for Web3 — audience mapping, KPI-based influencer and KOL campaigns, PR, community, and AI-search visibility so answer engines name your product. Full-market reach and AI-driven distribution, tracked to signups and activation.
Key Takeaways
- ✓Key features: Go-to-market for AI products, AI-influencer campaigns, AI-search visibility (AEO)
The engagement starts by naming the audience precisely. AI products routinely describe their market more broadly than they serve it, and that single imprecision propagates into creator selection, channel mix and messaging. Once the audience is named, we map the creators it already trusts — builders, reviewers and educators rather than general tech accounts — and structure KPI-based deals with them. Distribution then runs on three fronts at once.
Creator campaigns carry demonstration content, because AI buyers watch a product work before they sign up. PR and earned media supply the third-party credibility a self-serve buyer looks for while researching. AI-search visibility engineers the entity, schema and citations so answer engines name the product when buyers ask them for a recommendation — the channel where this audience is most likely to be asking. Attribution is wired in before any of it starts, so every channel is judged on activated users rather than traffic, and the instrumentation stays with you afterward.
Audience mapping first — AI products serve narrower audiences than their marketing usually assumes, and naming that audience precisely changes every downstream choice. Then KPI-based creator campaigns with the builders and educators that audience trusts, PR for credibility, community for the research phase buyers go through, and AI-search visibility so answer engines name the product. Everything reports to signups and activation.
Because your buyers are the population most likely to ask an AI tool for a recommendation. For a category where the buyer already lives inside these tools, being absent from the generated answer removes you from consideration before a comparison page is ever opened. The entity, schema and citation work is aimed squarely at that.
Builder-educators and reviewers — people who demonstrate a tool inside real work rather than describing it. AI buyers watch before they sign up, so a walkthrough or an honest comparison converts where a shout-out does not. Selection weights audience overlap and demonstrated conversion over follower count, and deals are KPI-structured like every other campaign here.
Attribution is wired in before campaigns start, so each creator, placement and channel is judged on activated users rather than clicks. The weekly report shows cost per activated user by source and what we are reallocating. The instrumentation is yours to keep afterward — the attribution setup, creator performance data and channel benchmarks that the engagement produced.
AIA practical growth playbook for AI startups — creators, PR, community, and being the product AI answer engines recommend.
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AIAI-powered creator matching, automated outreach at market scale, and promoting AI products through the right creators.
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AEOAnswer Engine Optimization for Web3 — how to be the project ChatGPT and Perplexity name.
7 min readTell us your targets and we’ll come back with a KPI-based plan — channels, creators, timeline and the reach you can expect.