Transcending time and space, you can talk with consumers and explore more opportunities and possibilities. That's why Opensurvey is building synthetic consumers.
When you hear "AI that answers like a consumer," everything sounds the same at first. Names like synthetic consumer, synthetic panel, and synthetic persona don't immediately reveal how they differ.
Here's how Opensurvey distinguishes the three.
Synthetic consumer is the umbrella concept. When you want to compare reactions across many consumers, you use the synthetic panel. When you want to explore the reasons behind a reaction from a single consumer's perspective, you use the synthetic persona.
Both start from the same real consumer data — but they answer different questions.
Synthetic consumers encompass two exploration experiences
Synthetic consumer is Opensurvey's umbrella term for AI-based virtual consumers built on real consumer data.
Within it are the synthetic panel, which simulates the reactions of many respondents, and the synthetic persona, a virtual individual with the perspective of a specific segment that you can talk to. Synthetic consumer isn't the name of a single feature — it's the concept that spans both experiences.
When comparing multiple candidates: the synthetic panel
The synthetic panel learns from real respondent data and answers new surveys at the individual-respondent level. In Concept Studio, it's used to compare multiple new product concepts and narrow down which candidates to bring into real consumer research.
Say your team has 20 new product concepts. You can't put all of them into a real consumer study, and narrowing them down through internal meetings alone leaves you short on evidence. This is where the synthetic panel lets you explore questions like:
Which concepts draw relatively stronger reactions?
How might reactions differ by target?
Which candidates deserve a closer look in real consumer research?
The core question of the synthetic panel is: "Which candidates should we look at further?" It compares the relative reactions of multiple candidates and narrows the options you carry into the next stage.
The output of a synthetic panel is not a launch decision — it's a set of priorities for the next round of validation. Final judgments about real purchase intent and product experience are confirmed with real consumer data.
When exploring the reasons behind reactions: the synthetic persona
Once you've narrowed the field, a "why" remains behind the numbers. Why did this concept look stronger? Which expressions built trust, and which parts created friction? What would change with a different target?
The synthetic persona is a way to explore these reasons by talking with a virtual individual who carries the traits of a specific segment. In DS AI, you can use it to examine a particular target's perspective and shape the questions to confirm in your next study.
You can ask a synthetic persona questions like:
What caught your eye first in this concept?
Which expressions are hard to understand or hard to believe?
In what situations would you actually need this product?
What should we confirm further in real consumer research?
The core question of the synthetic persona is: "Why might someone feel that way?" It explores the reasons and concerns behind reactions, sharpening both the concept and the follow-up questions.
A synthetic persona's answers are not quotes that represent the market — they're hypotheses to confirm in the next study.
The two at a glance
Synthetic Panel | Synthetic Persona | |
|---|---|---|
Core question | Which candidates should we look at further? | Why might someone feel that way? |
Form | Comparing reactions across many respondents | A conversation with one segment's perspective |
Best moment | When there are many candidates and you need priorities | When you're curious about the reasons and concerns behind the numbers |
Output | Relative comparison; a narrowed set of candidates | Explored reasons; hypotheses and follow-up questions |
Product context | Concept Studio | DS AI |
Principle of use | Use as priorities for the next validation | Use as hypotheses for the next validation |
The short version:
The synthetic panel narrows down which candidates to look at further; the synthetic persona explores why someone might feel that way.
They're most useful when you move between them
The synthetic panel and synthetic persona are currently separate product experiences, but they connect naturally within a single workflow.
Start in Concept Studio by comparing multiple candidates with the synthetic panel. Identify the candidates with strong reactions, the ambiguous ones, and the ones that split by target. Then move to Dataspace AI and talk with a synthetic persona to explore why those reactions might arise. Use the hypotheses you gain there to refine your concepts and survey questions, then confirm them in real consumer research.
The reverse direction works just as well. If a conversation with a synthetic persona surfaces a new hypothesis, you can turn it into several variations and compare them with the synthetic panel. For example, if a persona interview surfaces something like "cooking feels like a burden in the morning," you might write a few concept statements reflecting that insight and use the panel to see which one lands better. There's no fixed order — it's more about moving between the two tools depending on whether the question in your hands right now is a comparison or a why.
Facing many candidates? Use the synthetic panel. Facing the "why" left behind the numbers? Use the synthetic persona. Used together, the candidates and questions you bring to real consumers become far sharper.
That's why we bring these two experiences together under one name: the synthetic consumer.
Why We're Building Synthetic Consumers
Synthetic Panels to Compare, Synthetic Personas to Ask Why
How Opensurvey Builds Its Synthetic Personas
Heewon Park
Product Director, Opensurvey
Opensurvey
Opensurvey is an AI research tech company. We connect the entire research process—from research planning to data collection and analysis—with AI, and we offer a platform, expert research services, and a consumer panel all together. We work alongside industry-leading companies such as Samsung Electronics, P&G, CJ CheilJedang, and Woowa Brothers, and over the past 14 years we have served some 3,000 corporate clients across 25,000 projects. With ISMS-P, ISO/IEC 27001·27701, and ISO 20252 certifications, along with full membership in ESOMAR, we meet international standards in both security and research quality.
Dataspace
Dataspace is an AI-powered consumer intelligence platform provided by Opensurvey. An orchestrator that understands research context, together with specialized agents for each stage, accompanies the entire research process—from planning to data collection, analysis, insight reporting, and sharing. Its Dual Layer architecture, which separates statistical computation from AI inference, ensures analytical accuracy, and every insight is presented with evidence grounded in real consumer responses. You can connect with consumer panels in 20 countries including Korea, collect data directly from your own customers, or use APIs to integrate with external platforms such as CRM systems. The consumer data and research context accumulated in Dataspace remain as a company's intelligence asset. Building on this, you can create synthetic consumers tailored to your own brand to hold conversations with them and predict market responses.
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