Behavioral Data Creation for AI - Delivering Value and Insights
summary
Argues that owning high‑resolution first‑party behavioral events creates real competitive advantage, not just more data; Snowplow collects atomic event streams, validates and enriches them, then lands into Snowflake/BigQuery/Redshift or Databricks for DBT modeling and reverse‑ETL (Census/HighTouch) back to activation. Cites customers like Strava at 4 billion events a day and media personalization at DPG. Promotes a generate–enhance–model pipeline, claims gains: intelligible schemas, real‑time ingestion, better governance and faster feature engineering.
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chapters (6)
- 0:00Start
- 0:46My name is Alex Dean, I am co-founder and CEO of Snowplow
- 2:33The limitations of Data Exhaust
- 4:32Data Exhaust vs. Data Creation
- 5:16Data Creation offers technical and practical advantages over traditional data collection techniques
- 9:50What does Behavioral Data look like?
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