Building a Customer-Intelligence Brain: How GraphRAG Turns Data into Decisions
summary
Claims a working Customer-Intelligence system built by converting nine interviews into a Neo4j knowledge graph using the 12 Elements of Customer Progress Design, producing roughly 500 nodes and ~40 relation types. It wires GraphRAG and AI agents to run live queries that surface causal pushes/pulls, generate a prioritization heat map, novel need-based customer clusters, and a personalized 12-month support plan that a member wanted to sign up for, demonstrating the graph plus agents actually produce decision-ready evidence and automated deliverables.
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chapters (10)
- 0:00Introduction
- 1:03Defining the problem
- 2:03The case for knowledge graphs
- 5:26Building the graph
- 9:49Methodology and process
- 13:30Examining a practical example
- 16:44Discoveries through analysis
- 18:25Live demo and outputs
- 23:25Vision and future outlook
- 26:15Q&A and closing
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