> ## Documentation Index
> Fetch the complete documentation index at: https://docs.userintuition.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# In-depth Interview

> A focused conversation about what someone did, why they did it, and what they would change. No stimulus required.

An in-depth interview is a conversation and nothing else — no images, no links, no prototype. The moderator works through what someone did, why they did it, and what they'd change, following up on whatever turns out to be interesting.

It's the default study type, and the right one when you're still working out what the question is.

***

## When to use it

* **Discovery** — you're exploring a space and don't yet know what matters
* **Decision moments** — how someone chose between options, what happened after a bad experience, why they left
* **Before committing to a direction** — pressure-test the assumption before you spend six months on it
* **Unmet needs** — the frustrations people have stopped complaining about because they assume nothing can be done

If you have something specific to show people, you want a [Concept Test](/study-types/concept-test). If you have something for them to use, a [Prototype Test](/study-types/prototype-test).

***

## What a session looks like

The moderator opens on something concrete — a recent experience, a specific decision — and works outward from there. Rather than accepting the first answer, it follows up: what did you do next, what were you expecting, what would have changed your mind.

That laddering is where the value is. "The pricing was too high" is a data point. Three follow-ups later you find out they'd have paid double if the onboarding hadn't looked like a three-week project, which is a different problem entirely.

The moderator follows your research plan while adapting to each conversation, so every participant covers the same ground without every interview sounding identical.

***

## Setting one up

Nothing to attach. Tell Charles in [Step 2](/creating-a-study/customize-plan) who you want to talk to, what prompted the research, and what you'd do differently depending on the answer. He'll draft learning goals, key questions, and a conversation flow.

The single highest-leverage thing you can tell him is **what decision this research feeds**. A study designed to inform a specific decision asks sharper questions than one designed to "understand our customers."

<Tip>
  Share your hypotheses even when you're unsure of them. Charles can design questions that would disconfirm a belief — which is far more useful than questions that confirm it.
</Tip>

***

## Getting the most out of it

**Go narrow.** Four to six topics explored properly beats twelve skimmed. Interviews have a natural length, and every topic you add takes time from the others.

**Ask about what happened, not what people would do.** "Walk me through the last time you renewed" gets you behaviour. "Would you renew if we added X?" gets you a guess, and people are poor at predicting themselves.

**Let the unexpected run.** The most valuable moments are usually the ones nobody planned. The moderator will follow them, and your plan is a guide rather than a script.

***

## Frequently Asked Questions

<AccordionGroup>
  <Accordion title="Can I show an image in an in-depth interview?">
    Yes. In-depth interviews accept concept images too, so a conversation can turn into a concept test partway through if that's where it goes.
  </Accordion>

  <Accordion title="How long do interviews run?">
    It depends on your plan's scope — most land between 10 and 25 minutes. Charles includes time estimates per section so you can see the shape before you launch.
  </Accordion>

  <Accordion title="Which interview format should I use?">
    Voice, in most cases. Spoken answers run longer and reveal more than typed ones, and it costs half what video does. See [Interview modes](/getting-started/interview-modes).
  </Accordion>

  <Accordion title="How many interviews do I need?">
    It depends on how common the thing you're looking for is. Twelve to twenty covers most discovery work, but if you're hunting something that affects 1 in 10 participants you'll want closer to 30. Work out your number with the [sample size calculator](/resources/sample-size).
  </Accordion>
</AccordionGroup>
