Case Study: 8tracks achieves real-time recommendations and scalable data science with Domino Data Lab

How Domino fuels data science at 8tracks

8tracks, one of the world’s largest radio-playlist services with over two million streamable playlists and direct licensing partnerships, wanted to use data science to improve recommendations, reporting, and operational efficiency without hiring a large in-house team. Their challenges included deploying real-time predictive models, giving non-technical teams self-service reporting, and running compute-intensive analyses on scalable infrastructure.

Using Domino, 8tracks’ small data-science team quickly published models as REST APIs for real-time recommendations, built self-service report Launchers for marketing and label partners, and spun up powerful cloud machines (e.g., 32‑core, 240 GB) for heavy training and A/B analysis. The result: faster model iteration and automated retraining, huge time and cost savings (delivering outcomes that would have required roughly twice the staff), better user experiences, and increased customer acquisition and retention.

8tracks

Rémi Gabillet

CTO