Case Study: Paytronix achieves real-time data science and faster transformations with Coalesce

A Better Approach to Data Science Helps Paytronix Offer Better Guest Engagement

Paytronix, a restaurant and retail marketing software company, needed a better way to turn siloed data from many sources into actionable insights for guest engagement. Its data science team was slowed by a patchwork of custom Scala and PySpark jobs, long learning curves, and weeks-long pipeline development, making it hard to experiment quickly or deliver real-time value to customers.

To solve this, Paytronix implemented Coalesce with Snowflake, using Fivetran HVR for ingestion, Coalesce for data transformation, and Snowpark for near real-time modeling. With Coalesce, the team cut last-mile transformation costs by 50%, reduced pipeline build time from weeks to 2–3 days, and had two new employees complete a major transformation project in one month instead of the entire team spending six months with little progress.

Paytronix

Jesse Marshall

Director of Data Science