Yotpo
eCommerce front-runner speeds up analytics, and simplifies pipeline maintenance with Boomi, improving governance, data access, and accruing monthly time-savings.
Business goals
Yotpo, a Forbes Cloud 100 eCommerce marketing platform, helps global brands build high-converting, data-driven experiences across reviews, loyalty, SMS, and subscriptions, integrating with leading martech stacks. With 100+ internal users in R&D, customer success, support, and engineering, Yotpo wanted to unify data from embedded products and client systems for BI tools including Looker and Tableau.
The company needed to streamline data flow, democratize governed access, and implement a centralized, self-service integration layer to reduce engineering dependency and accelerate analytics.
Integration Challenges
Yotpo needed fast, reliable data movement and transformation for Looker/Tableau. However, a patchwork of tools caused delays, schema conflicts, and high costs.
Data was manually staged in S3, processed in Spark, and written to Databricks. Schema mismatches broke pipelines, while the Delta table loader was costly, and unreliable.
Every added tool increased complexity, and technical debt. Without a unified integration layer, time-to-insight slowed, resources were strained, and governance suffered.
How Boomi Helped
After failed attempts with three tools, Yotpo adopted Boomi Data Integration to unify pipelines, and simplify operations. Boomi delivers native Databricks connectivity (removing intermediate steps), rapid table onboarding in minutes, and custom REST connectors for services like Opsgenie.
Role-based access enables a data mesh model, while Snowflake integration grants secure access to non-admins (e.g., HR analysts). An intuitive UI and broad connector library let business users build and maintain flows, easing engineering load.
Results
Boomi empowered Yotpo to centralize its data stack, cut tools and costs, and improved scalability. Key benefits include adding Databricks tables in minutes, eliminating complex pipeline maintenance (saving hours monthly), wider self-service adoption by nontechnical teams, an HR-built standalone data product without engineering help, and simplified governance with democratized analytics access across the organization.
