Case Study: Outreach achieves faster ETL and improved ML-driven sales efficiency with Databricks

Outreach - Customer Case Study

Outreach.io, a sales engagement platform that helps reps prioritize and engage prospects using machine learning (for example, classifying customer intent from emails), faced growing challenges as it ingested large volumes of diverse data—emails, unstructured, streaming, and time series—daily. Managing Spark on EMR was complex and resource intensive, data pipelines demanded excessive engineering effort, and ML development lacked repeatable, reproducible processes, causing delays and operational overhead.

Databricks provided a fully managed analytics platform with automated cluster management, faster ETL performance, MLflow for reproducible model lifecycles, and a collaborative workspace for data scientists. The result: ETL jobs that once took weeks now run in days, faster time to market, increased data science productivity, and more reliable machine‑learning features that help sales teams work smarter and close more deals.

Outreach

Yong Liu

Principal Data Scientist