Minds PRISM: Our Approach to Synthetic Market Research

PRISM is how Minds turns audience knowledge into useful research conversations. It combines grounded AI personas, reusable audiences, and structured simulations so teams can explore how different people may interpret a concept, respond to a message, or weigh a trade-off.

The aim is simple: help teams learn earlier. Instead of asking one generic assistant to speak for a market, Minds creates a group of distinct respondents and lets researchers examine both shared patterns and meaningful differences.

The underlying academic method is silicon sampling: conditioning large language models on respondent profiles, asking survey-style questions, and comparing the resulting distributions against human survey data. PRISM is how Minds operationalises that method for commercial synthetic research — the grounding, the audience construction, and the validation that turn a research technique into a repeatable workflow.

Start with individual Minds

A Mind is a reusable AI persona shaped by a clear description and the context available to the workspace. Depending on configuration, that context can include profiles, research notes, links, files, and permitted public-source material.

Each Mind keeps its own perspective, priorities, knowledge, and constraints. This gives a simulation multiple points of view rather than one averaged customer voice.

Build an audience, not a stereotype

Minds are combined into Audiences designed around a real research question: a buyer group, customer segment, user type, market, or decision context. Teams can review the Audience, refine its composition, and reuse it across Studies.

The result is a working research population with individual respondents behind the aggregate. Researchers can compare segments, inspect specific answers, and see where an apparent consensus hides important disagreement.

Run structured simulations

In a Study, every Mind can react to the same concepts, questions, messages, images, or trade-offs. Minds supports qualitative prompts and structured question formats, with configured research methods available where enabled.

This makes PRISM useful for work such as:

• concept and message exploration;
• positioning and proposition development;
• objection and language discovery;
• early pricing and packaging research;
• audience and segment comparison; and
• preparing stronger questionnaires, interviews, or live tests.

Responses remain available for review, so teams can move from a high-level pattern back to the reasoning and language behind it.

Use simulation to make better research decisions

PRISM is designed for fast, directional learning. It helps teams test more options, expose weak assumptions, and narrow the questions worth taking into human research.

Synthetic responses are not automatically representative market estimates or observed behavior. When a decision requires external proof, teams should validate it with recruited participants, behavioral data, experiments, or specialist review.

That combination is the Minds approach: use synthetic research to explore broadly and quickly, then apply human evidence where the decision demands it.

Read Inside Minds: How Synthetic Research Panels Are Built for the complete workflow, or see the completed Reality Benchmark for public validation results.