Structured vs. Unstructured Data

Not all data lives in a spreadsheet. Structured data (numbers, categories) is easy to report on. But unstructured data (feedback, emails, recordings) can unlock deeper insights if you know how to use it.

Why it's Important

Founders often miss insights hiding in qualitative data.
Many early decisions rely on understanding user sentiment.
Combining both data types gives you richer context.
Unstructured data helps validate what structured data suggests.
It builds a more complete picture of your product's performance.

How to Implement

Categorize your data sources (CRM, support tickets, Slack, interviews).
Use simple tagging systems for unstructured data (themes, tones).
Set up templates to collect feedback consistently (Google Forms, Typeform).
Use AI tools to summarize or cluster text-based input.
Translate unstructured insights into hypotheses for testing.
Connect structured and unstructured data in dashboards or reports.
Set up regular reviews of support/chat/email logs.

Available Workshops

Data Source Mapping: Inventory all structured and unstructured sources.
Feedback Tagging Practice: Tag real support tickets by theme.
Quote Wall: Post unfiltered user feedback in your workspace.
Structured → Insight Drilldown: Match metrics to related feedback.
Interview Debrief Sprint: Turn call transcripts into key findings.
Data Story Fusion: Mix one metric with three quotes to create insight.

Deliverables

A map of structured and unstructured data sources.
Tagging taxonomy or category list for unstructured feedback.
Feedback-to-metric linkage template.
A monthly “insights report” combining both data types.
System for collecting and storing interview data and chat logs.

How to Measure

% of feedback tagged or categorized.
Time to process and summarize unstructured feedback.
Number of insights derived from unstructured data.
Uptake of unstructured insights in product decisions.
Trends or patterns found by merging both data types.
Quality of insights shared during retros or sprint planning.
Feedback loop turnaround time from input to action.

Real-World Examples

Zapier

Built user voice into product planning by tagging all feedback by feature.

Figma

Used support ticket themes to guide feature rollouts during beta.

Duolingo

Analyzed user reviews and in-app behavior together to identify learning friction points.

Get It Right

Build lightweight tagging systems early.
Encourage all teams to contribute feedback insights.
Regularly compare qualitative and quantitative data.
Use real quotes to humanize reports.
Make unstructured insights part of planning rituals.

Don't Make These Mistakes

Ignoring support tickets because they’re “not data.”
Letting interviews pile up without processing.
Creating dashboards that exclude unstructured insights.
Avoiding qualitative work because it’s “hard to scale.”
Storing feedback without organizing it for future use.