01Synthetic consumer research
Test concepts, claims, key visuals and packaging with AI personas or digital twins of real people. Results in minutes instead of weeks.
02What changes
03Two kinds of respondents
Every study runs on one of two panel types. Both answer in their own words, and both are built for consumer brands.
Dynamic Personas
Dynamic Personas are our synthetic consumers. Panels are drawn from official population statistics and matched to your target group. Every persona gets a complete life story before it answers a single question of yours.
Premium Twins
BetaPremium Twins are digital twins of real consumers in Germany, Austria and Switzerland, built from in-depth interviews about their lives, routines and shopping. The twin answers your study the way the person behind it would.
04How it works
01 / 04 — Ask
Put your question to the Research Agent in plain language. It drafts the study with you: research question, questionnaire and stimuli such as packshots or concept boards.
› question: “Which pack design wins with young families?”
02 / 04 — Panel
Describe your target group in your own words, for example “health-conscious parents in cities”. The agent turns that into panel criteria and draws a matching panel.
› panel: n = 100 · quota-matched · DE 18+
03 / 04 — Field
The panel answers in its own words, and the agent follows up where it gets interesting. You get the numbers and the reasons behind them, in your audience's own language.
› field: 100/100 responses · open answers probed
04 / 04 — Evidence
You get an executive summary, results per question, the key themes and a clear recommendation, ready for your next meeting.
› report: summary · themes · recommendation ✓
05Proof
A selection of our references
06The platform
A language model can imitate a shopper in seconds. Getting from there to research you would put in front of your board takes a lot more: panels built on real statistics, methods that have been tested, a source for every finding, and constant checking.
Plans the study with you, runs it and writes the report. One conversation from question to result.
Builds the right study design for any question: method, questionnaire and stimuli, matched to the decision in front of you.
Dynamic Personas and Premium Twins, each with a documented origin: data vintage, method and model version.
From concept and claim tests to pricing and assortment questions: proven research methods, extended all the time.
Your briefs, past studies and brand guidelines feed into every study as context.
Every step of the pipeline is evaluated continuously. Improvements ship only after human review.
The web app for your whole team, plus interfaces to plug theconsumer.ai into your own tools.
07Why it's different
Most synthetic research builds a respondent from a statistical profile and a prompt. That mostly reproduces what the statistics already know. With us, every respondent has a life story before it answers. Research backs this: agents grounded in interviews about people’s lives simulate individuals considerably more accurately than agents built from demographics alone (Park et al., 2026).
| Traditional research | Generic AI | Statistical synthetic panels | theconsumer.ai | |
|---|---|---|---|---|
| Time to result | 2–6 weeks | Seconds | Minutes | Minutes |
| Grounded in | Real respondents | Whatever the model learned | Statistical profile and prompt | Official statistics and a life story per respondent |
| Depth per respondent | High, but costly | None | A row of attributes | A coherent life story |
| Real people behind it | Yes | No | No | Optional, with Premium Twins |
| Scale answers | Measured | Picked by the model | Often picked by the model | Measured with SSR |
| Traceability | Report | None | Summary | Every number and quote linked to its answers |
Comparison of typical approaches, not of individual providers.
08Use cases
Teams use it before the concept board goes to management, before the pack goes to print and before the pitch goes to the retailer.
09Company
We combine market research, AI and experience from international brands so that every team understands the people it decides for.
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