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Test your
Price before going to market.

SCL creates synthetic populations that mirror real consumer behavior. Test your price, your product, your campaign — any scenario on your mind — in minutes, without going into the field.

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GROUNDED IN SCIENCE Our approach runs on proven LLM simulation models. Browse the articles
How it works

Consumer research in three steps.
No fieldwork.
Digital twins instead.

01

Create your population

Choose from more than 50 attributes such as age, income, city, and habits — build a synthetic sample with exactly the profile you need, or use the ready-made nationally representative sample of Türkiye.

02

Design your study

Surveys, conjoint, A/B tests, focus groups. Write your questions, define your scenario, and run it — all within minutes.

03

Get your insights

Demand curves, crosstabs, theme and sentiment analysis. Reports appear on your screen the moment the study finishes.

Use cases

A method for every question on your mind.

Quantitative and qualitative — on the same synthetic population, on the same day.

Pricing
Measure willingness to pay and find the optimal price point.
Conjoint analysis
Simulate real competitive dynamics and build your strategy.
A/B testing
Which variant wins, and why? Image uploads supported.
Focus group — single room
Chat with your target audience in real time.
Focus group — multi-room
Split your audience into subgroups and ask each room different questions.
Demand elasticity
See the reaction to a price change before you run the campaign.
Feature analysis
Which features stand out — and which are worth paying for?
Packaging & design testing
Upload variants and measure attention instantly.
Advertising & campaign testing
Validate your message before it goes live.
Multiple-choice surveys
Large-scale quantitative studies, in minutes.
Why synthetic

Fieldwork is great.
Waiting isn't.

Traditional research takes weeks, struggles with niche samples, and is costly to repeat. Synthetic populations solve all three problems at once.


Reliable, validated data.

Talk to AI models tested against thousands of real consumers and calibrated weekly.

Fast

Synthetic consumers respond instantly. Set up a study in the morning and have the report by noon.

Flexible

You define every attribute, from social media usage to city of residence. Even the most niche audience takes only a few clicks to build.

Repeatable

Change an assumption, rerun the same study, and compare the results side by side. That's how scenario testing should work.

FAQ

Frequently asked questions

Synthetic personas are digital twins built on demographic, socio-economic, and behavioral data inspired by real consumers. On the sampling screen you can choose any combination of attributes, or use a ready-made sample that matches Türkiye's population distribution. They are not real consumers — they simply behave remarkably like the real thing.

In quantitative and multiple-choice studies, SCL results are regularly benchmarked against real field data and deviation margins are calculated. In qualitative studies, a topic-overlap method matches real research findings with SCL outputs on a theme-by-theme basis.

It depends on the research type: quantitative reports include demand and revenue curves with breakdowns by segment, income, education, and age; qualitative reports include summaries of findings, clustering, and theme and sentiment analyses; multiple-choice reports include frequency and breakdown tables. All analyses are available directly on your screen.

A focus group can be run with even a single synthetic persona. For other research types, we recommend a sample of at least 100 personas.

Quantitative research relies on numerical data: pricing tests, willingness to pay, A/B tests. Qualitative research focuses on understanding opinions, preferences, and behaviors in depth: focus groups, customer journey analyses.

Within minutes. The moment your research is complete, the report appears on your screen — no waiting, no scheduling.

Ask your question.

Start today with 50 Person-Question credits. No setup, no waiting.

Design lab
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