360° customer view
Redshift to Salesforce
Redshift to Customer.io
Clearbit is a B2B SaaS company that provides tools to improve sales & marketing efforts by aggregating public data about customers. Clearbit started by offering a lead enrichment API (taking an email address and returning data like location, job title, etc.) and has since added a number of products to its suite like lead prospecting (returning contact information for leads based on a customer's target parameters).
Because of Clearbit’s multiple products, fast growth, and large user base, they needed a way to automate a lot of their own sales & marketing and personalize every customer interaction. Specifically, they needed to have a clear picture of what all their users were doing across their suite of tools and they needed this available in Salesforce and Customer.io.
That’s when the Clearbit Data team turned to Census for help.
The Clearbit team was generating lots of raw product usage events but they were spread across 9+ products. Each product in the suite has its own unique user identifier, which means that activity wasn’t de-duplicated. In addition, they couldn’t correlate these user activities with the data in their marketing & sales tools so it was impossible to act on the data. Here’s some specific examples of the challenges they faced:
The data team was spending a lot of time cleaning all this data to build accurate reports but none of this work was reflected back in their sales & marketing tools. This was when they turned to Census to share their single source of truth from their data warehouse to all their other tools and give their teams internal customer data they could rely on for their processes, workflows, and automations.
The first step for the data team was to build out a sustainable architecture to ingest, store, model, and analyze all their events & data. Before they could set out to unify all their user schemas and data sources, they pulled in raw data using Segment & Stitch Data into their Redshift warehouse. On top of these raw tables, they built custom logic in SQL for de-duplicating users that appear in all their Segment sources & SaaS tools. These models also generate insights & customer attributes that are useful to the business. They leverage DBT to write these models and store them in a version-controlled repository.
With Census, in less than a week, they were able to sync this model to Salesforce & Customer.io without requiring any help from the engineering team.
Now that Census was up and running, every time the data team added new metrics or facets to their customer model, they could make it available to the sales & marketing teams directly using Census' visual mapper.
Finally, the data team keeps control of the data flow from the ETL all the way to the tools which allow them to ensure data quality and accuracy.
By syncing attribution data to a custom object via Census, the data team gave the sales reps the power to see all of the leads' touch points and where in the journey they converted to a MQL or SQL.
With this information always up to date in Salesforce, the Ops team could also quickly run reports and see which offers, acquisition channels or campaigns were performing the best by tying it to actual deal closed and revenue.
With data aggregated customer data and metrics syncing to Customer.io, the marketing team can leverage that data to build granular segmentation of Clearbit’s large userbase to send personalized email messages such as:
With Census syncing the unified customer profile that has 100+ fields to both Customer.io and Salesforce, all of the commercial teams at Clearbit spend less time troubleshooting bad data or dealing with duplicate users and more time operationalizing the data.
Finally, Sales Representatives don’t have to keep multiple tabs open such as internal apps, BI tools and payment providers to understand how their accounts are using Clearbit, where they came from and best to grow these accounts.
Thanks to Census and the work of Clearbit's data team, the sales & marketing teams now have more data at their fingertips in the tools they use every day to understand their customers and create powerful, personalized campaigns.
The greater benefit has been how the culture of the company has changed to be more deeply data-driven and the virtuous loop that has emerged between the data team and the rest of the organization. Now that more teams rely on live data in a way that impacts revenue growth, there’s an implicit Quality Assurance (QA) feedback loop that helps the data team improve quality & accuracy.