Behavioural datasets, ready to query
Aggregated behavioural features built from first-party consented activity, delivered as native tables through Snowflake and Databricks. There is no pipeline to build and no raw event rows to process, just derived signals ready to join to your own data.
CPG Beauty and Personal Care Personas
Individual-level beauty and personal care profiles where purchase and digital behaviour sit on the same person, across eight surfaces including TikTok Shop. One row per person, with every tagged event resolved to exactly one of twenty categories.
- 376
- Features per profile
- 20
- Categories
- GB, US
- Markets
- Quarterly
- Refreshed
Snowflake Marketplace, Databricks Marketplace
View datasetCPG Beverage Personas
Individual-level beverage profiles where purchase and digital behaviour sit on the same person. One row per person, with every tagged event resolved to exactly one category, so category shares partition cleanly and per-category spend adds up to the total.
- 306
- Features per profile
- 13
- Beverage categories
- GB, US
- Markets
- Quarterly
- Refreshed
Snowflake Marketplace, Databricks Marketplace
View datasetDigital Personas
Cross-platform behavioural profiles describing how one person behaves across twelve digital surfaces, from browsing and search to social, AI assistants and retail. One row per person, aggregated over a full year.
- 12
- Surfaces per market
- 670 to 732
- Features per profile
- US, GB
- Markets
- Quarterly
- Refreshed
Snowflake Marketplace, Databricks Marketplace
View datasetGLP-1 Journey Personas
Individual-level GLP-1 behavioural profiles, built from what consented participants searched, browsed, asked an AI assistant, and bought. One row per person, with treatment state, adoption barriers and journey timing derived from observed activity rather than claims data.
- 194
- Features per profile
- 6
- Treatment states
- GB, US
- Markets
- Quarterly
- Refreshed
Snowflake Marketplace, Databricks Marketplace
View dataset