Case Study: HOMER increases student engagement and reduces churn with Databricks

Closing the early education gap with data

HOMER is an early‑childhood education company that builds learning experiences for kids ages 2–8. Despite being digitally native, HOMER’s data was fragmented across disparate systems, preventing cross‑team collaboration, an accurate view of students, and the analytics needed to personalize learning and reduce churn.

By centralizing their data on the Databricks Lakehouse (Delta Lake) and using MLflow for model delivery, HOMER stood up a unified data platform in six months and pushed initial models to production in about six weeks. The new ETL, segmentation and churn‑prediction pipelines delivered near‑real‑time insights that increased student engagement, lowered churn, improved conversion by 1–5%, and drove an estimated revenue impact of up to $20M while enabling broader operational and product decisions.

HOMER

Jin Chung

Senior Director of Data Insights