Methodology
What synthetic audiences are, how Tesemble uses them, and where they stop.
This matters more for Tesemble than for most software. Here is exactly what we claim, and what we don't.
Methodology
Simulation, not synthetic certainty.
Tesemble is designed for hypothesis generation and prioritization, not as a replacement for conversations with real customers.
Synthetic audiences help you explore a larger hypothesis space quickly. The strongest hypotheses should then be validated using real-world experiments.
Synthetic personas are not real people. What they give you is a structured, repeatable way to compare how a defined audience is likely to react to competing ideas, so that the expensive part of GTM (talking to real customers) starts from a shorter list.
Simulate broadly. Validate honestly.
How a simulation runs
- Input context
- Persona definition
- Controlled stimuli
- Multiple simulated responses
- Aggregation
- Segment comparison
- Hypothesis prioritization
What we're building toward
- Confidence ranges
- Repeated simulations
- Prompt and version tracking
- Model diversity
- Experiment reproducibility
- Calibration against real-world outcomes
Why not just use ChatGPT?
A simulation is more than asking an LLM a question 100 times.
Asking a model to “pretend to be 50 customers” gives you 50 answers. Tesemble gives you a controlled experiment across a defined audience.
FAQ
The questions people actually ask.
What is a synthetic audience?
A set of AI-generated personas defined by attributes you choose: role, industry, company size, geography, buying behaviour, pain points, existing alternatives. You expose the whole audience to the same stimulus and compare how responses differ across segments.
Are synthetic personas real people?
No. They are simulated respondents. Tesemble never claims they are a substitute for real customers.
Does Tesemble replace customer interviews?
No. It helps you prioritize what to validate with customers. Use it to narrow a wide set of hypotheses to the few worth the cost of real-world testing.
Where do the personas come from?
You define them. Personas are constructed from the B2B or B2C attributes you specify, combined with the context you provide about your product and market. Tesemble then generates many individual respondents that fit that definition.
How accurate are simulations?
Simulations are not predictions of what an individual will do. They surface directional patterns across a defined audience: which message a segment prefers, which objections recur, where segments diverge. Treat the output as a prioritized set of hypotheses, then validate the strongest ones with real customers.
Can I create my own personas?
Yes. Defining your own audience is the second step of every simulation.
Can I upload my own customer research?
Not yet. Today you bring context through your website, product briefs and GTM messages. Uploading your own research is on the roadmap.
Which AI models does Tesemble use?
Tesemble uses large language models to generate persona responses. The value is in the layer around them: defined audience distributions, controlled stimuli, aggregation across many respondents and segment-level comparison.
Is my company data used to train models?
No. Your briefs, personas and results are used only to run your simulations.
Can I compare multiple hypotheses?
Yes. That is central to the product. Run competing messages, positionings or offers across the same audience and compare them side by side.
You've got more GTM ideas than you can test.