Top Use Cases for Synthetic User Research
Using AI-powered synthetic user research to help public service teams make faster, fairer, and more informed decisions.
In our last blog, we introduced the idea of synthetic user research: using AI-generated “representatives” built from real data to scale and accelerate qualitative insight. But what does this look like in practice?
Here, we explore the top use cases where synthetic user panels can add the most value.

1. Rapid Options Appraisal
Decision-making often involves weighing up competing options - whether for policy design, digital service models, or operational processes. Traditionally, this requires new rounds of engagement or lengthy analysis.
Synthetic user panels change the game. By asking representatives to score each option against pre-defined criteria (such as cost, usability, or fairness), teams can:
- Overcome the neutral response bias among traditional audiences
- Leverage AI representatives to support decision-making, in situations where qualitative nuance isn’t as important
- Use insights from discovery work later in the project life-cycle/policy options stage
In one The PSC pilot, synthetic scores closely matched real workshop results, demonstrating the method’s reliability in option appraisal.
2. Ensuring Balance Across Stakeholders
Traditional qualitative analysis risks giving disproportionate weight to the most articulate or vocal participants. If you’ve just left a focus group or workshop worried that a few people dominated the conversation, synthetic representatives help redress this balance by:
- Representing the full spectrum of views within each stakeholder group.
- Ensuring minority perspectives are not lost in synthesis.
- Producing outputs that reflect the group as a whole, rather than just a few dominant voices.
This makes findings more representative, transparent, and fair.
3. Making Sense of Consultations and Calls for Evidence
Policymakers often run large-scale consultations or public calls for evidence to shape future decisions. These exercises can generate hundreds or even thousands of submissions, each filled with detailed perspectives, arguments, and data. Turning this volume of information into actionable insights is a significant challenge.
Synthetic user research provides a new way forward:
- Synthesising diverse inputs – Composite representatives can be generated for different respondent groups (e.g., industry, civil society, individual citizens).
- Balancing perspectives – Ensures that no single lobby or highly vocal respondent dominates the analysis, giving fair weight to quieter or emerging voices.
- Accelerating the policy cycle – Instead of months of manual coding and thematic analysis, synthetic representatives deliver draft insights in days. Moreover, once the policy area is further refined/developed, the voices from consultation representatives can be ‘brought back in’.
This makes it possible for policymakers to move from raw consultation responses to clear, evidence-based policy implications far more quickly - without losing the nuance of real voices.
Synthetic user research is not a silver bullet, and it doesn’t replace human judgement. But it does provide faster, more balanced, and more scalable ways of turning raw voices into insight. The examples here show ideal testbeds to begin experimenting with synthetic representatives.
If you’d like to discuss this with our team, get in touch at hello@thepsc.co.uk.
Latest News & Insights.
The Next 20: Rethinking Demand – The Role of High Intensity User Services in Urgent and Emergency Care
How the British Red Cross's HIU services are helping shift urgent and emergency…
The Neighbourhood Health Framework: what it means for systems and leaders
The Neighbourhood Health Framework explained – key goals, delivery models and…
The Next 20: Bringing mental health care closer to home
In this episode of The PSC in Conversation, Harris Lorie and Mikoto Nakajima…