From Journeys to Systems: Rethinking Customer Experience with Knowledge Graphs
summary
Claims that customer journeys become live, queryable graphs rather than static maps, implemented with Neo4j/Aura and Cypher and modeled as five node types (touchpoint, data, system, team, value). Examples include finding a single point of failure with betweenness 0.76, tracing PII capture without consent, performing cluster analysis to reveal siloed onboarding/payment flows, and following data lineage for customer ID; system metadata shows things like 99.5% uptime and dependent services.
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chapters (5)
- 0:00Introduction
- 1:29Flaws of customer journey maps
- 3:40Knowledge graphs vs journey maps
- 9:45Queries and analyses possible
- 14:56Combining both approaches
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