Understanding Insights in Customer Discovery
Insights are the core unit of learning in your customer discovery process.
An Insight is a structured piece of evidence derived from your interviews — based on either:
- a transcript (from recorded conversations), or
- notes (manual observations)
Each insight captures something meaningful from a customer conversation and connects it directly to your Canvas hypotheses.
Why Insights Matter
Customer discovery is not about collecting interviews — it’s about making decisions based on evidence.
Insights help you:
- Capture the exact voice of the customer
- Avoid relying on memory or assumptions
- Link real evidence to your hypotheses
- Systematically evaluate whether your assumptions are valid
👉 Without insights, your Canvas is just a set of ideas
👉 With insights, it becomes an evidence-backed system
Where Insights Come From
Insights can be created in two ways:
1. AI-Generated Insights
When an interview includes a transcript, the platform can automatically generate insights by analyzing the full conversation.
These insights:
- Highlight key signals from the interview
- Capture both direct statements and deeper patterns
- Serve as a strong starting point for your analysis
2. Manual Insights
You can also create insights yourself from:
- Interview transcripts
- Notes
This allows you to capture:
- Important quotes
- Observations
- Context-specific interpretations
How to Create an Insight (Manual Workflow)
Step 1: Select Evidence
Highlight a section of text from:
- the transcript
- or your notes
Once selected, it appears in the Insight panel.
Step 2: Link to a Hypothesis
Choose one or more Canvas hypotheses.
This step is critical — it connects your observation directly to a specific assumption.
Step 3: Mark the Direction
Indicate whether the insight:
- Supports the hypothesis
- Challenges the hypothesis
Step 4: Add Comment (Optional)
Add a short explanation to capture why this insight matters.
You can also:
Tags (Optional but Recommended)
Tags help you organize and group insights across interviews. Tags are AI-generated and apply automatically to insights.
You can use tags to:
- Identify recurring themes
- Highlight important signals
- Mark ideas worth exploring further
For example:
- A “New Hypothesis” tag may indicate something not yet captured in your Canvas
Tags are fully customizable and can be adapted to your workflow.
Step 5: Set Priority (Optional)
If an insight is particularly important or actionable, assign a priority level to help you focus on high-impact findings.
Step 6: Save
Click Save to store the insight.
It will appear in your Insights list and can be reviewed anytime.
How Insights Are Structured
Each insight is more than a note — it is a structured object that includes:
- A specific piece of evidence (quote or observation)
- A clear interpretation
- A link to one or more Canvas hypotheses
- A support or challenge indication
- Optional tags and priority
👉 This structure ensures every conclusion can be traced back to real data.
Working with Insights
Once created, insights can be:
- Viewed in the Insights list
- Played back (if linked to transcript audio)
- Edited or refined
- Deleted if no longer relevant
All insights — both AI-generated and manual — are collected in the Insights View, where you can:
- Review evidence across interviews
- Filter and organize insights
- Identify patterns
- Spot gaps in your data
How Insights Connect to Your Canvas
When insights are linked to hypotheses:
- Your Canvas begins to show evidence counts
- You can see which assumptions are supported or challenged
This allows you to:
- Review all related evidence
- Identify patterns across interviews
- Decide whether to:
- Validate
- Revise
- Invalidate a hypothesis
Key Takeaway
Insights are the bridge between:
👉 What customers say
👉 What you believe
They transform your Canvas from a static set of ideas into a dynamic, evidence-based system.
The more structured and consistent your insights are, the stronger your decisions will be.