Single Customer View
summary
A Single Customer View is built end-to-end here: a Play server captures events, pushes them to Kafka → S3 + real-time processors, Spark builds sessionization and deduplication, and merged profiles land in DynamoDB with analytics in Redshift. The pipeline handles 10–20 million events/day (scale to hundreds of millions), performs near‑real‑time identity resolution and enrichment, and drives predictive suggestions (for example surfacing e‑signature fields)—the system runs in production and serves product and marketing actions.
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chapters (7)
- 0:00Introduction to single customer view
- 3:24Why context matters in user tracking
- 7:17Building the single customer view pipeline
- 10:06Scalability and real-time challenges
- 12:56Benefits of owning customer intelligence
- 13:40Technical architecture overview
- 14:22Q&A session
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