Theme Analysis
Categorizing customer feedback into recurring topics and patterns.
Category
Analytics & Insights
Full Definition
Theme analysis (or thematic analysis) is the process of categorizing customer feedback into recurring topics, patterns, and categories. It transforms unstructured feedback into organized, quantifiable insights.
How Theme Analysis Works: 1. Theme Definition: Establish categories relevant to your business 2. Coding: Assign feedback to appropriate themes 3. Quantification: Count and track theme frequency 4. Trending: Monitor how themes change over time 5. Action: Address most impactful themes
Common Theme Categories: - Product quality - Service experience - Staff behavior - Wait times - Pricing/value - Cleanliness - Accessibility - Communication
Common Use Cases
Real-World Examples
Scenario
A spa categorizes feedback into themes. This month: "Massage pressure" (35 mentions, 80% positive), "Booking process" (28 mentions, 40% positive), "Locker room cleanliness" (22 mentions, 25% positive).
Outcome
Massage services are a strength. They focus improvement on the booking system and locker room, not the treatments.
Scenario
An airline tracks themes monthly. "Seat comfort" complaints spike 40% after installing new economy seats.
Outcome
Before the spike becomes public relations disaster, they add extra cushioning and legroom on affected routes.
Scenario
A software company tracks feedback themes: "Ease of use" (stable at 45% positive), "Customer support" (dropped from 70% to 45% positive over 3 months).
Outcome
They investigate and find they outsourced support during that period. They bring support back in-house.
Related Terms
Text Analytics
The process of extracting meaningful insights from unstructured text feedback.
Sentiment Analysis
AI-powered analysis of text to determine whether feedback is positive, negative, or neutral.
Verbatim Feedback
Word-for-word customer comments captured through open-ended survey questions.