Reflect's journey analysis framework
Reflect's customer journey framework combines three methods: real-time observation of online behavior, AI classification of decision narratives and experimental design. Together they give a picture of how customers actually buy — not how they say they do.
We have developed an integrated framework for customer journey analysis that goes beyond traditional methods. The framework has three components that complement each other.
The first component is real-time observation via Journey Decision Engine. Respondents navigate real websites and apps while we capture every click, comparison and channel switch. The data shows the actual purchase journey — not a reconstruction after the fact.
The second component is AI classification of decision narratives. Respondents describe their purchase decision in their own words. AI analyzes thousands of narratives and identifies decision themes, motivation, barriers and triggers. The classification provides structure without losing nuance.
The third component is experimental design. We manipulate specific variables — price, product information, channel experience — and measure the effect on decisions. This gives causal answers to questions that observation and narratives alone cannot answer.
The three components together give a picture that no single method can deliver. Observation shows what customers do. Narratives show how they think. Experiments show what actually drives decisions.
Key takeaways
- Three components: observation, AI narrative analysis, experimentation
- Journey Decision Engine captures real online purchase behavior
- AI classification structures thousands of decision narratives
- Experimental design isolates causal drivers
- The methods complement each other for a complete picture