Clearbit's marketing attribution model: how we built a single view of our customers

Clearbit has implemented a single-source attribution model, developed by their Head of Analytics, Julie Beynon, to accurately measure the impact of marketing activities by tracking customer interactions across multiple channels and products. Before this model, Clearbit struggled with fragmented data that hindered their ability to determine which marketing campaigns were most effective. The new model integrates data from over ten sources, including ads, emails, and events, allowing sales and marketing teams to access customer journey insights directly within tools like Salesforce. This enables more personalized and effective customer interactions, as well as intent scoring for leads. The model operates on Redshift and utilizes dbt for data transformation, ensuring that complex data inputs are simplified and accessible to non-technical team members. This comprehensive approach not only enhances the understanding of individual customer journeys but also informs strategic decisions to improve marketing efficiency and effectiveness.