Finding Patterns in Data
Identify themes and trends across your research data
Your Progress
Section 3 of 5Look for Patterns
Organized data is just the starting point. Now you need to find themes, trends, and patterns that reveal what matters most.
Patterns are signals. They tell you what to prioritize and where to focus product efforts.
Recognition Techniques
Pattern Recognition Techniques
Frequency Analysis
Count how often themes appear
Track how many users mention each theme
12 of 15 users mentioned slow performance
High frequency = high priority issue
Avoid Biases
Analysis Red Flags
⚠️ Outlier Bias
One extreme opinion does not represent all users
⚠️ Confirmation Bias
Seeing only data that supports your beliefs
⚠️ Recency Bias
Over-weighting the most recent research
⚠️ Loudest Voice Bias
Prioritizing vocal users over silent majority
Balance Frequency with Impact
Not all patterns are equal. A problem mentioned by 3 enterprise users might be more valuable than one mentioned by 20 free users. Consider both frequency and business impact.
Key Takeaways
- •Use frequency, sentiment, workflow, and segment analysis to find patterns.
- •Watch for biases like outliers, confirmation, recency, and loudest voice.
- •Balance pattern frequency with business impact when prioritizing.