The Art of the Follow-Up Question
The most valuable insights usually come from the second or third question. Here is how to dig deeper.
In user research, the first answer is rarely the whole truth.
Interviewer: "Do you like this design?" User: "Yes, it's nice."
If you stop there, you have learned nothing. "Nice" is a polite filler word. It's a dead end.
A skilled researcher knows that the gold is buried deeper. You need to dig.
The "5 Whys" Technique
This is a classic root-cause analysis method, but it works beautifully for interviews.
- User: "I don't use the export feature."
- Why?: "It's too complicated."
- Why?: "I have to choose between CSV and PDF and I don't know which one I need."
- Why?: "My boss just asked for a 'report' and I don't know what format he wants."
- Why?: "He usually prints them out for meetings."
Insight: The user doesn't need a "CSV export." They need a "Print-ready report."
How AI Does This at Scale
Training a team of humans to ask "Why?" consistently is hard. They get tired. They forget. They feel awkward prying.
AI doesn't have social anxiety. In Fieldrun, we prompt our AI agents to be "curiously persistent."
If a participant gives a one-word answer, the AI is trained to say:
- "Could you say a bit more about that?"
- "What specifically makes you feel that way?"
- "Can you give me an example of when that happened?"
Examples from the Field
We ran a test comparing a standard form vs. an AI interview about a banking app.
Standard Form Question: "What is your biggest frustration?" Typical Answer: "Login is slow."
AI Interview: AI: "What is your biggest frustration?" User: "Login is slow." AI: "I hear you. Is it the loading time of the app itself, or the authentication steps like FaceID?" User: "It's the 2FA. It takes forever to get the SMS code."
Result: The problem wasn't the app speed (engineering issue); it was the SMS provider (vendor issue).
The follow-up question changed the entire solution.