A market research method that uses AI and live in-market experiments to gather real evidence of customer behavior and purchase decisions, without recruiting survey panels.
Most concept testing answers a shallow question: which variant wins? The version that's worth doing reveals what your customers actually want.
Surveys predict purchase intent at 20 to 30% accuracy. Stack five decisions on that foundation and the math falls apart fast.
Fast is not useful if it is wrong. Why grounding synthetic personas in live experiments beats survey-trained bots.
Everything worth knowing before you put surveys behind you, no jargon, no hedging.
Evidence of what customers actually do, verified clicks, purchases and choices observed in live markets, rather than what they say they'll do in a survey or focus group.
Surveys predict real purchase behavior only 20 to 30% of the time. Heatseeker calibrates its predictions to up to 95% correlation with verified behavior.
An AI model of a customer segment trained on verified behavioral data and your own first-party data, not scraped web text. You can question it directly and get an answer in minutes.
A/B testing optimises one asset for one metric. Heatseeking reveals the deeper drivers behind a decision, jobs to be done, pain points, pricing, language-market fit, and feeds them into a private model of your market.
Synthetic experiments return a behavior-backed read in minutes. Live in-market experiments return statistically significant proof in days, not weeks or months.
No. Your synthetic audience is trained only on your tests, your first-party data and your behavioral signals. No one else gets access to it.
The thinking, experiments and results behind behavior-first marketing, written for operators, not algorithms. Straight to your inbox, no fluff.
See behavioral ground truth on your own question in a 15-minute demo.
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