Discovery Interview Plan

Purpose

Guide product managers through preparing for customer discovery interviews by asking adaptive questions about research goals, customer segments, constraints, and methodologies. Use this to design effective interview plans, craft targeted questions, avoid common biases, and maximize learning from limited customer access—ensuring discovery interviews yield actionable insights rather than confirmation bias or surface-level feedback.

This is not a script generator—it's a strategic prep process that outputs a tailored interview plan with methodology, question framework, and success criteria.

Key Concepts

The Discovery Interview Prep Flow

An interactive process that:

1. Gathers product/problem context (marketing materials, assumptions)
2. Defines research goals (what you're trying to learn)
3. Identifies target customer segment and access constraints
4. Recommends interview methodology (Jobs-to-be-Done, problem validation, switch interviews, etc.)
5. Generates interview framework with questions, biases to avoid, and success metrics

Why This Works

• Goal-driven: Aligns interview approach to what you need to learn
• Adaptive: Adjusts methodology based on product stage (idea vs. existing product) and access constraints
• Bias-aware: Highlights common pitfalls (leading questions, confirmation bias, solution-first thinking)
• Actionable: Outputs interview guide ready to use

Anti-Patterns (What This Is NOT)

• Not a user testing script: Discovery = learning problems; testing = validating solutions
• Not a sales demo: Don't pitch—listen and learn
• Not surveys at scale: Deep qualitative interviews (5-10 people), not broad surveys (100+ people)

When to Use This

• Starting product discovery (validating problem space)
• Repositioning an existing product (understanding new market)
• Investigating churn or drop-off (retention interviews)
• Evaluating feature ideas before building
• Preparing for customer development sprints

When NOT to Use This

• User testing a prototype (use usability testing frameworks instead)
• Quantitative research at scale (use surveys, analytics)
• When you already know the problem (move to solution validation)