The platform

One platform. Two engines. Every customer decision.

Heatseeker pairs always-on synthetic personas with live in-market experiments, both grounded in your first-party data, both calibrated against real behavior. Predict in minutes, prove in days.

Two engines

Predict in minutes. Prove in days.

● Synthetic · answers in minutes

Put your customer on demand

Turn your own data into a customer you can question directly. Ask anything and get an answer in minutes, or run synthetic experiments at a fraction of the cost of fieldwork.

Every experiment sharpens the persona. Your team owns a compounding customer view and the evidence to act on it, not a deck that expires.

Built for a practice, not a project.

Shared workspaces, shared personas, one standard for how decisions get evidenced.

A synthetic persona answering in its own words
● In-market · proof in days

Know what your market will do

Real experiments with real audiences show what customers actually do, not what they say. Plan, design and launch live ads with Heatseeker AI; proof from the market in days.

Real ads running live in market under a lookalike brand
How it works

From a growth question to a decision, built, run and analyzed for you.

Step 01
Ask your growth question

“Which positioning wins the male skincare segment?” Plain language in.

Step 02
We build the test

Heatseeker proposes the audience and designs the experiment from your site & data.

Step 03
It goes live

Experiments run on Meta & LinkedIn, branded or under a lookalike brand, against real buyers.

Step 04
Get the answer

The decision, the evidence behind it, and your next best experiment, ready to act on.

Questions teams bring us
  • Which positioning wins the male skincare segment?
  • Which of these three fee structures do customers actually choose?
  • Do our buyers want this feature, or do they want it explained better?
  • Which onboarding promise gets people to finish sign up?
Proof you can audit

Every answer traces back to real buyers making real choices.

We measure revealed preference, the choices people actually make, not survey-stated intent. Here's the method, the sampling, and how confidence is calculated.

01
Run it in market

Ad variants go live to real audiences on Meta and LinkedIn. We measure revealed preference: the choices people actually make, not survey-stated intent.

02
Validate statistically

Each result is tested for statistical significance before it informs a persona. A typical experiment gathers tens of thousands of impressions and hundreds to thousands of engaged responses.

03
Calibrate and score

Persona answers are grounded in that behavioral data, each carrying a confidence score derived from sample size, effect size, and consistency across experiments.

What you can audit

Every persona answer is fully traceable.

  • Sample size on every experiment
  • Exact audience definition and targeting
  • Statistical significance / confidence interval
  • The experiments behind any single answer, traceable by ID
20 to 30×
faster than traditional research
What the evidence changed

A bank was certain its brand should be built on human led customer support. Tested as a concept, it lost. In every market. To “set up an account in less than 10 minutes.”

The losing concept revealed the real driver: speed to value. Before the rebrand, not after.

Read what the losing concept revealed →
The foundation

The Customer Context Layer.

Everything Heatseeker learns about your brand, kept and compounding, CRM, transactions, performance marketing and research, all in one view. The two engines feed it, and it makes both of them smarter. The longer you run, the sharper every answer gets.

  • First-party data in, one customer view out
  • Refreshed weekly or daily by plan
  • Never used to train third-party models
Calibration & Evals

Every prediction is checked against real outcomes; every answer scored for accuracy, up to 95% correlation to real behavior. Evidence trustworthy enough to act on.

Compounding advantage

Each experiment sharpens the next. Your context layer becomes a moat competitors can't buy off the shelf.

Works with your stack

Live inside the AI tools your team already uses.

LLMs generate; Heatseeker validates. Through MCP, your assistant can ask Heatseeker to predict and prove, and get evidence back, not guesses. It's the difference between a fluent answer and AI market research you can trust.

Claude, Gemini & GPT

Connect via MCP so your assistant validates positioning, pricing and product decisions against real behavior in the flow of work.

Meta & LinkedIn

Live experiments run on the platforms your buyers are actually on, branded or under a lookalike brand.

Your data sources

CRM, transactions, loyalty and performance marketing flow into one compounding customer view.

More than an A/B test

We don't optimize ads. We answer the questions behind your strategy.

Real ads are the instrument, the way we observe genuine behavior at scale. Every experiment is built around a strategic question, and the output is a decision: who your audience really is, what they value, and what they'll do.

Value Proposition

Which promise actually moves your market.

Feature

Which capabilities customers will pay for.

Buying Drivers

What truly drives the decision to buy.

Strategic Horizons

Where the next big bet should be placed.

Language-Market Fit

The exact words that land in each market.

Who it's for

Built for the people who own the number.

How Heatseeker fits each role, and the proof each one walks into the room with.

See the platform on your own decision.

Bring a live question. We'll show you both engines working on it.

Book a 30-minute demo →