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Qualitative Research at Scale

Run hundreds of in-depth interviews simultaneously with AI facilitation

Qualitative research has always forced a trade-off. If you want depth — rich, behavioral data from real conversations — you work with small samples. A skilled researcher can conduct five or six in-depth interviews per day. At that rate, 50 interviews is a significant investment of time, and the analysis takes weeks more.

If you want scale, you move to surveys. But surveys can only find what you thought to ask for. They can't probe. They can't follow a thread. They can't distinguish between a confident answer and a hedged one.

Signal Sessions resolve that trade-off.

Depth at the scale of surveys

Savo runs AI-facilitated interviews in parallel. You can field 50 or 500 interviews with the same campaign, all at the same time, producing comparable structured output from every session. Every participant gets a one-on-one conversation with consistent facilitation — adaptive, probe-oriented, non-evaluative — regardless of how many sessions are running simultaneously.

The interviews produce transcripts, evidence units, and dimension scores. You don't get back a pile of recordings to code. You get structured, scored data with full traceability to the underlying language.

Scientific rigor built in

Qualitative research is most useful when it's defensible. Savo's methodology is built around the standards that make research defensible:

Pre-specified dimensions — What you're measuring is defined in advance, with behavioral anchors that specify what evidence counts as signal. This is the foundation of dimension validity, and it's where most AI conversation tools skip a step.

Calibrated scoring — Scoring rubrics are human-authored and calibrated against reference sets. The same passage scores the same way regardless of which session or run processes it.

Evidence gating — If a conversation doesn't produce enough evidence to score a dimension reliably, the system abstains rather than generating a plausible-looking score. Abstention is informative. A confabulated middle score is not.

Full traceability — Every insight links to the evidence that produced it. You can show your clients, your peer reviewers, or your stakeholders exactly what participants said and how scores were derived.

The research workflow

  1. Design your event — Define your research question, the dimensions you're measuring, and the interview protocol in Event Studio. Or start from a reference event in the Signal Event Library.
  2. Launch your campaign — Set your participant list, schedule, and session length. The wizard takes about 10 minutes.
  3. Sessions run — Participants complete their sessions on their own schedule, in their own environment, without a researcher present.
  4. Analyze your results — Scored insights appear in your Insights report as sessions complete. Key Dimensions, Intersections, and Emergent Patterns surface the findings. Evidence Explorer gives you full drill-down to source language.

For a deeper look at Savo's methodology, see The Science Behind Signal Sessions. For how to read and use your results, see Reading Your Insights Dashboard.