Project Broadcast
SaaS company increased customer LTV by $667K, reduced churn, and accelerated analytics by unlocking insights across data sources.
ビジネス目標
Project Broadcast, a fast-growing SMS/MMS automation platform provider, needed to unlock actionable insights from product usage data stored in MongoDB. To improve retention and customer lifetime value, the company sought a modern data stack that could support data-driven decisions across the business. It also required a scalable solution to onboard new sources like marketing, CRM, and ads data, while integrating seamlessly with dbt Cloud and Snowflake to power analytics and long-term growth.
連携における課題
Project Broadcast’s fragmented, self-managed data stack created major operational and analytics bottlenecks:
- Frequent Meltano/Prefect failures requiring manual backfills of 1–2M records
- Slow onboarding of new data sources
- Limited product and marketing visibility due to MongoDB’s structure
- Heavy maintenance and infrastructure burden on a small team
These issues increased costs, reduced agility, and prevented the company from fully leveraging data to drive retention, innovation, and growth.
Boomiによる解決
Project Broadcast deployed Boomi Data Integration to replace its legacy data stack and automate end-to-end analytics. Boomi centralized product data from MongoDB, marketing data from Google and Facebook Ads, sales and customer data from HubSpot and Google Sheets, and piped everything into Snowflake for warehousing and Sigma for analytics. Replacing Meltano and Prefect, Boomi also integrated with dbt Cloud, giving the small team a fully managed, scalable solution without infrastructure overhead.
成果
With Boomi, Project Broadcast achieved major operational and business improvements:
- Eliminated manual backfills and heavy maintenance
- Scaled from 1 to 8 data sources in six months
- Increased customer LTV by $667K through improved retention and upsells
- Reduced churn by identifying key usage patterns
- Enabled a small team to manage complex pipelines with ease
Boomi consolidated ingestion, orchestration, and transformation, freeing teams to focus on innovation rather than maintenance.
