Case Study: Zip unifies audience segmentation with dbt Labs and dbt Cloud

Zip unifies audience segmentation with Snowflake, Census, and dbt Cloud

Zip, a fast-growing banking and financial services company, needed a better way to unify customer data across teams and channels. Their growth, product, and marketing teams struggled to use the same segmented audiences consistently in tools like Braze and the Zip app, and they needed more reliable self-service access to data. To support this, Zip evaluated several modern data stack components and chose dbt Cloud from dbt Labs for transformation.

With dbt Labs’ dbt Cloud as the transformation layer, Zip built a modern data stack centered on Snowflake, Snowplow, Fivetran, and Census. The team now has 1,000+ dbt models in production after 18 months, improved documentation and dependency management, and enabled non-technical users to build and sync unified audiences for more granular targeting. According to Zip, this has made data more trusted and actionable across the business, while supporting scalability and future growth.

Zip

Moss Pauly

Senior Product Manager