Strategic Recommendations
Early-stage AI company · Strategic research

Finding the market for an AI product
Two phases of primary research and a deep secondary scan, built to help an early-stage AI company understand its market, its users, and where the real opportunity sits.
Role
Project Lead
Context and objective
Conviction, not yet evidence
An early-stage AI company needed to understand the market it was entering before it committed to a direction. It had a product and a strong point of view, but not yet a clear, evidence-based picture of who its users really were, what they needed, and where the genuine opportunity sat in a crowded and fast-moving category.
The objective was to replace assumption with evidence. Success looked like a founding team that could make product and go-to-market decisions with confidence, grounded in what the market actually wanted rather than what the team hoped it would.
Approach and key insights
How the work unfolded
As Project Lead, I owned the engagement end to end and ran it in two phases, directing the research from design through synthesis. It began with a deep secondary scan to map the category, the competitive landscape, and the forces shaping demand, which sharpened the questions worth asking. From there I designed and led two phases of primary research, taking the emerging picture back into the field to test it, deepen it, and pressure-test the assumptions the team was carrying. Throughout, I worked directly with the founders to translate what we were learning into decisions, and kept the research tied to the choices in front of them rather than to interesting but idle findings.
The value was less in any single finding and more in the shift from a founder's conviction to a shared, evidence-based view of the market. The research separated the needs that were real and urgent from the ones that only sounded compelling, clarified who the product was genuinely for, and gave the team a defensible basis for where to focus first.
Duration
16 weeks,
two phases
Industry
User Experience
Artificial Intelligence
Engagement
Strategic Research
Timeline
2026
Deliverables
What was produced
The work moved from a broad secondary scan to focused primary research across two phases, each output built to sharpen the next decision.
Secondary Research Synthesis
Product Strategy and Feature Proritisation
User and Demand Insights
The return showed up in sharper decisions and a founding team that could move with real evidence behind it.
What changed
Impact
A shared, evidence-based view of the market
Sharper positioning and a clearer target user
A de-risked product and go-to-market direction
Assumptions replaced with defensible findings
Primary Research, Phase One
Market and Category Map
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