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Synthetic data in market research
Synthetic data in market research means you interview simulated respondents instead of recruiting humans. Use it to screen questions, messages, and concepts. Queued studies return in about 15 minutes. Every study is calibrated against published survey data before it reaches you. The calibrated 50-state benchmark: 7.07-point average miss on the best 80% of 1,521 scored questions (1,216 retained). 10.02 points across every scored question. A narrower April test on 5 places with 10,000 respondents scored 7.47 points on 404 non-electoral questions. File a probability sample when the design has to stand on its own.
Two meanings of "synthetic data"
In analytics, synthetic data often means a privacy-safe clone of a customer table. In research, it means a panel that never sat in a facility. Lewsearch is the second. Every study is calibrated against published survey data before it reaches you. The calibrated 50-state benchmark: 7.07-point average miss on the best 80% of 1,521 scored questions (1,216 retained). 10.02 points across every scored question. A narrower April test on 5 places with 10,000 respondents scored 7.47 points on 404 non-electoral questions. Coverage: coverage (650,000 census-grounded respondents · all 50 states and D.C. · 16 occupation panels.). Method: methodology.
Worked example: spend the human budget once
A live focus group usually tests one creative direction and takes weeks to recruit. A team can run the same instrument on a synthetic panel first, drop the confused option, and take one cleaned concept into the facility.
| Job | Synthetic panel | Human sample |
|---|---|---|
| Message / concept screen | Fit. Minutes, published MAE | Optional second pass |
| Instrument lint (leading, double-barreled) | Fit. Cheap to re-run | Wasteful as a first find |
| Legal or press poll | Not fit | Required |
| Rare clinical or highly specialized users | Directional only unless you have a scored analog | Recruit the actual population |
FAQ
- What is synthetic data in market research?
- Answers generated by a model that stands in for a human panel. In Lewsearch's case the respondents are census-grounded and the aggregate is scored against real polls. It is not imputed missing rows in a customer file.
- When should I use it?
- Message tests, concept screens, instrument linting, and multi-market directional reads before you spend on humans. A traditional focus group takes weeks to recruit. A queued synthetic study returns in about 15 minutes.
- When should I not use it?
- Legal, regulatory, or published journalism samples that require a probability design. Every Lewsearch report states the data are AI-generated.
- How do I know the synthetic data is any good?
- Every study is calibrated against published survey data before it reaches you. The calibrated 50-state benchmark: 7.07-point average miss on the best 80% of 1,521 scored questions (1,216 retained). 10.02 points across every scored question. A narrower April test on 5 places with 10,000 respondents scored 7.47 points on 404 non-electoral questions. See /methodology.
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