The evidence

Where every claim comes from

Before we ask you to trust synthetic, here is the full trail: one real study end to end, human vs synthetic theme by theme, and how we audit it.

Evidence trail, not black-box insight

From brief, to synthetic conversation, to a traceable theme.

Before we ask you to trust synthetic research, we show you where the output comes from. This is one real study, end to end.

Client brief

"Why do customers stay with their insurer even when they are unhappy?"

Internal hypothesis: Price is the main barrier.

Audience: Spanish insurance customers, mixed age and income segments.

Guide: Switching triggers, trust, coverage understanding, reactions to renewal messaging.

Verbatim from the study
Interviewer

What stops you from switching insurer, even when you are not happy?

Synthetic respondent

"Price is the brake. Complexity is the fog. The fog is worse — it stops me from even seeing the road."

Theme detected

Complexity blocks switching more than price.

Mapped across 217 synthetic interviews — strongest where coverage feels hardest to compare.

Decision changed

The brief shifted before fieldwork.

From "test price messaging" to "probe clarity, trust, and rejection of scare tactics".

Real study · Spain 2026

What 217 Spanish insurance consumers actually said

Insurance Coverage Choice — Spain 2026. N=217 synthetic consumers. SHQI 0.989.

A client needed to understand why Spanish consumers stay with their insurer even when unhappy — and what triggers switching. The internal hypothesis: price is the main barrier. They ran 217 synthetic consumer interviews in under 30 minutes.

What the study found:
  • Fear-based upsell was the #1 rejected pattern — 125 mentions, 0 acceptances across all 217 respondents
  • Mapfre dominated spontaneous recall with 530 mentions — 2.2× more than any competitor
  • "Complexity is the fog" — consumers could not evaluate coverage options, so they stayed put by default
The hypothesis was wrong — price was not the primary barrier.

The real blocker was complexity and distrust of scare tactics. The brief shifted from price messaging to transparency and simplicity — before a single real interview started.

Before

Hypothesis: price is the main barrier.

After

Real blocker: complexity and distrust of scare tactics.

Result

The fieldwork guide was rewritten before a single real interview — before any of the budget was spent on the wrong questions.

Human vs synthetic

You don't have to "believe" in synthetic.

See where it aligns with humans. And where it doesn't.

Mirror View runs the same interview guide on humans and synthetics and compares them side by side — mention rates, themes, sentiment. Same analysis pipeline, same metrics. You ship convergence and divergence, not AI claims.

Live example: hybrid study, ChatGPT productivity

3 human + 18 synthetic respondents, same guide, real convergence.

Real dashboard excerpt, data anonymised.
Efficiency (driver)
Human 67%
Synthetic 61%
High convergence
Accuracy concerns (barrier)
Human 33%
Synthetic 28%
Aligned
Learning curve (barrier)
Human 33%
Synthetic 17%
Divergence — worth probing
Why this matters
  • Same interview guide and analysis pipeline for humans and synthetics — comparable outputs.
  • Quotes and evidence trace back to conversation transcripts, not free-floating AI summaries.
  • Use synthetic for coverage and speed; use humans when live validation is required.
Why researchers trust the output

Built to be audited, not believed.

Every claim on this page maps to something you can inspect — not an AI wrapper that asks for faith.

  • SHQI — 12 deterministic quality metrics, no LLM in the scoring loop
  • Mirror View — human vs synthetic on the same guide and pipeline
  • Every theme linked back to the conversation that produced it
  • Full transcript export — read the raw evidence yourself
  • Population back-tested against real-world survey data (World Values Survey)
  • Honest about limits — we show you where synthetic diverges from human
We use it on ourselves

We pressure-tested this very page with QualiSynth.

Before publishing, we ran synthetic interviews with agency researchers in the US, UK and Spain — the exact buyers this page is for.

Finding

One finding: buyers thought QualiSynth analysed their own transcripts, instead of generating respondents.

Resolution

That's why this page now leads with the mechanism. Directional, fast, and honest about its limits — exactly how we'd want you to use it.

Ready to run it on your own study?