Know what consumers actually do.
Where do customers buy instead? Which creators reach them? What do they compare before buying? Our AI agents answer the questions across marketing, category and strategy with real behavioral evidence. Ask, inspect the data and follow up.
Which TikTok users actually buy afterwards, and how do they differ from heavy users who never convert?
The data is there: TikTok sessions, product searches, Amazon orders. Starting four agents in parallel.
Bartholomew mapped the question onto the panel schema.
Andrey cut 845M TikTok events into converters and heavy users who never buy.
Fridtjof checked the category against public market data.
Erasmus built the report from it: 6 sections, 5 charts, sources.
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Decisions happen every day. Consumer evidence should too.
Questions go unanswered
Category decides what to stock. Marketing decides where to spend. Strategy decides which markets to enter. Each decision benefits from knowing more about consumers. But teams cannot commission a study for every question.
The evidence is already there
29,000 consumers choose to share their searches, purchases and media habits with us, and get paid for it. General Evidence connects those records so teams can investigate what consumers do, including beyond their own website.
What using it actually feels like.
Ask. Inspect the evidence. Keep going.
Investigate audiences, purchase journeys and competitors in one workspace. Agents analyze the records; you inspect the findings and follow up. Reports make the evidence easy to share. Below is an illustrated view and a real study you can read in full.
What Gen Z buys on Amazon after TikTok, and what millennials do instead
Built by the Research Agent · n = 4,120 panellists · census weightedGen Z converts on beauty and fashion within two weeks; millennials convert later, and mostly on electronics.
“I saw it three times before I looked it up. By then I already wanted it.”
Not claimed. Observed.
Other panels know that a purchase happened. We see the whole path to it: every search, every review, every ad, every price comparison. And the moment someone switches brands.
And we can ask at every step.
Consumer intelligence in your daily work.
Ask where customers go, what they compare or which media they use. Agents investigate the linked records. Inspect the findings and follow up until you have evidence you can act on.
How does the customer journey for espresso machines differ between MediaMarkt and Amazon?
Every team asks something different.
The real journey, observed step by step. No journey reconstructed from memory weeks later. Observed paths, step by step.
The data comes from the people it belongs to.
People connect accounts through our apps, Datapods and Stack, and get paid for sharing. Connections can bring years of history; regular updates extend the record. We link searches, purchases and media use into a dataset our agents can investigate.
Verified through connected accounts
Purchases, searches and media use come from the source, not self-reporting.Paid through the data dividend
Sharing data earns money. Daily, transparent, fair.Disconnectable at any time
Every source can be revoked with one tap. GDPR-native, EU-hosted.
Clean data. Shared on purpose.
Every data source in the panel is a conscious decision: connected source by source, paid through the data dividend, revocable at any time.
EU-hosted, GDPR-native
Processed in the EU and built to European law from the start, not retrofitted into compliance.Never used to train open models
Panel data does not leave the platform as training material. No exceptions, no small print.Revocable at any time
Every source can be disconnected with one tap, and nothing after that point is collected.Real consumer behavior, fresh from the panel.
Daily-updated statistics on consumption, digital habits and media: from 29,000+ consenting panelists in Germany. Citable, free, no signup.
Ask your first question this week.
Bring a question from your daily work. See what consumer evidence can add to the decision.
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