Back to AI library

Skill

Interview script format

Write unbiased, well-structured customer interview scripts with this AI skill. Use it when preparing a new script or revising questions before an interview.

Open this AI skill

About this AI skill

The Interview script format skill is pre-built for Elle (the AI assistant in Aha! software) and provides a consistent structure for customer interviews. Elle reviews your draft script and learning objectives, rewrites leading questions, and organizes the script into five stages, from introduction to closing. It outputs a numbered script with follow-up probes, questions to cut if time runs short, and notes on which learning objectives the questions cover or leave unanswered.

The full Interview script format skill, as Elle uses it:

# Interview script format

Use when writing or revising a customer interview script so the questions stay neutral and produce evidence you can act on.

## Definitions

Use these meanings consistently in every step.

- **Neutral question:** A question that does not signal the answer the interviewer wants and does not name a solution
- **Leading question:** A question that embeds an assumption, a preference, or a proposed solution. "How frustrating is the current export?" is leading. "Walk me through the last time you exported data" is not.
- **Probe:** A follow-up that goes deeper on what the participant just said, without introducing a new idea
- **Script stages:** Introduction, contextual questions, exploration questions, validation questions, and closing

## Workflow

1. Read the draft script and identify what the study is trying to learn. When that is not stated, ask before revising.
2. Rewrite every leading question as a neutral one. Prefer questions about specific past behavior over questions about hypothetical preference.
3. Order the questions across the five script stages, moving from broad context to specific topics
4. Number every question sequentially, regardless of type, so the interviewer can reference them during the session
5. Add a probe under each exploration question. Probes ask for the last time it happened, what the participant did next, or what they tried first.
6. Remove jargon and internal product names. A participant who has to decode the question answers a different question.
7. Check the balance. A script weighted toward validation confirms what the team already believes. Flag that when you see it.
8. Note which questions map to which learning objective, and name any objective the script does not cover

## Rules

- Ask about past behavior rather than future intent. "Would you use this?" produces unreliable answers.
- No question names a solution the team is considering
- No question contains two questions. Split compound questions.
- Keep the script to a length that fits the session, and say which questions to cut first when time runs short
- Headers use sentence case. No em dashes, en dashes, or curly quotes.

## Output

```
## Learning objectives  
- <what this interview needs to answer>  
  
## Script  
### 1. Introduction  
<rapport and purpose, and consent to record>  
  
### 2. Contextual questions  
1. <question>  
  
### 3. Exploration questions  
2. <question>  
 - Probe: <follow-up>  
  
### 4. Validation questions  
3. <question>  
  
### 5. Closing  
<invite additional thoughts and explain next steps>  
  
## Cut first if short on time  
- <question numbers, in order>  
  
## Objectives not covered  
- <objective, and what question would cover it>
```

## Quality checks

- No question signals a preferred answer or names a proposed solution
- Every exploration question has a probe
- Questions move from broad to specific across the five stages
- Every learning objective maps to at least one question, or is listed as not covered

Try this AI skill now

Open the Interview script format skill in Aha! Discovery to structure your customer interview script and rewrite leading questions as neutral ones.

Open this AI skill

About Elle

Elle , the AI assistant in Aha! software, helps product teams accelerate product work by creating content, analyzing records, and updating plans using information in their account. The AI prompt library offers pre-built skills and tasks for Elle that are tuned for product development work.