Case Study: Paytronix achieves real-time predictive analytics with Fivetran

Paytronix boosts customer loyalty with real-time data science powered by Fivetran and Coalesce

Paytronix, a customer engagement platform for restaurants and convenience stores, needed a faster, more reliable way to collect and act on data from many disparate systems. Its legacy ingestion tool missed transactions and its hand-built Scala and PySpark transformation jobs were difficult to maintain, slowing down the data team’s ability to experiment, build pipelines quickly, and deliver trusted insights.

With Fivetran, Paytronix centralized near-real-time data from 12 connectors into Snowflake, then used Coalesce and Snowpark to automate transformations and run predictive models without moving data out of Snowflake. The result was faster time to insights, one source of truth, and real-time predictive analytics for client campaigns; the company also reported that two new team members completed a high-profile transformation in one month, versus six months with the old approach.

Paytronix

Jesse Marshall

Director of Data Science