BlaBlaCar
Global car-pooling marketplace accelerates marketing data ingestion across multiple ad platforms, cutting setup to half a day, saving 64+ hours of manual work.
Business goals
BlaBlaCar, a long‑distance carpooling platform leader, connects 100+ million drivers and passengers in 22 countries. To scale marketing analytics, it required efficient ingestion of high-volume campaign data from Google, Facebook, etc. Priorities included fresher data, less manual coding, and automated schema management for reporting.
Faced with rapidly changing advertising APIs, BlaBlaCar needed a scalable and dependable data ingestion pipeline. To accelerate data-driven decisions, minimize maintenance, enhance reporting accuracy, facilitate growth, and efficiently manage cross-channel attribution, and performance tracking at scale.
Integration Challenges
BlaBlaCar’s developers spent excessive time hand-coding ingestion pipelines, constantly updating Python scripts for schema changes, and maintaining brittle connections across multiple ad platforms. Limited connector coverage slowed onboarding and integration. Frequent API schema changes triggered recurring disruptions and delays.
Existing tools were costly or misaligned with pricing needs. Manual processes blocked analysts and produced inefficient workflows. Collectively, these issues hampered BlaBlaCar’s ability to quickly collect and analyze campaign data, undermining marketing.
How Boomi Helped
BlaBlaCar sought an API ingestion tool and chose Boomi Data Integration after finding it offered broader marketing connectors and robust REST API support. Boomi automated detection and handling of API schema changes, supported key ad platforms and BigQuery, and enabled pipelines to be built in half a day.
Easy field mapping and monitoring empowered engineers and analysts. By unifying integration in one platform, Boomi replaced manual processes, accelerated ingestion, and delivered faster, more reliable data to BI tools like Tableau.
Results
Boomi Data Integration slashed BlaBlaCar’s marketing data ingestion time from weeks to half a day. It saved 64+ hours of manual coding, reduced Facebook Ads migration from months to one week, and enabled complex multi-API pipelines in a single day.
Boomi became the default for all ingestion, freeing the team to explore use cases like reverse ETL, boosting time-to-insight, and marketing ROI.
