Heatseeker

Heatseeker is an analytics tool. Heatseeker runs live market experiments and turns the observed response into synthetic personas that predict how a defined audience will react to product stories, propositions and campaign creative. Brand, insights, product and growth teams use it to narrow options before spending, and predictions are compared against real behavior.

Heatseeker is a customer evidence platform built for teams that need to make growth decisions before committing budget. Instead of relying on panels, surveys or a general purpose language model's hunch about what an audience wants, it runs live experiments in market and uses the observed response to train AI customer models it calls synthetic personas. You define an audience, put competing hypotheses in front of real people as ads, and read the resulting response as evidence rather than opinion. The workflow follows a loop: predict with the persona, test in the market, then learn by comparing the prediction against what actually happened. Connected campaign and shopping results add further evidence over time, and Heatseeker is explicit that importing data does not by itself validate a prediction. A separate market scan layer listens to social media and product reviews so the next question originates from what people are already saying, with the intent that a scan ends in an experiment rather than a static report. The tool suits brand, insights, product and growth teams that want to work from one shared customer model and one body of evidence. DoorDash's team reports using it to narrow eight creatives down to two before a paid social push, and L'Oréal's digital chief frames it as a way to explore ideas before customers see them. The company also publishes a retrospective study of 11 live market experiments comparing leading AI models with observed behavior, while noting that study evaluates general models rather than Heatseeker's own persona accuracy. Compared with AI research chatbots that simulate a customer in conversation, Heatseeker's differentiator is the grounding step: the persona is informed by real market response, and predictions are checked against reality. Buyers should note that the homepage is careful about what a result proves. A response shows what people reacted to, not why, and not what they will purchase. The product is positioned for enterprise-scale decision making, with SOC 2 Type II, GDPR and AES-256 listed, and pricing is arranged through a demo rather than self-serve checkout.