Loop optimizes Snowflake costs across thousands of embedded analytics users

SELECT provided comprehensive cost visibility with an intuitive diagnostic flow. The platform's automated insights enabled confident warehouse rightsizing decisions and early identification of expensive workloads. Regular monitoring through SELECT became integrated into Loop's operational routine, providing quantitative foundation for cross-team cost conversations and architectural decisions.

Loop operates a sophisticated data infrastructure platform with Snowflake serving as the central warehouse for both internal operations and customer-facing analytics. The platform supports thousands of external users through embedded analytics in their returns management application, while internally serving 100s of internal users across multiple tools. The internal user base spans five analytics engineers developing in dbt, three analysts setting up workbench reports, and machine learning engineers building Streamlit applications for foundational merchant comparison models and recommendation systems. Beyond traditional analytics, Snowflake powers operational use cases including automated merchant alerts that trigger when merchants leverage key features, enabling customer success teams to proactively reach out and understand issues.

Before SELECT, Loop operated under a 'no holds barred' philosophy during their initial Snowflake adoption, prioritizing maximum value extraction from data insights over cost management. This approach enabled rapid innovation and data platform development but provided limited visibility into spending patterns and optimization opportunities. As Loop began preparing for Snowflake contract renewal conversations, they recognized the need for systematic cost monitoring and right-sizing.

Through SELECT's Automated Savings feature, Loop was able to immediately lower their spend by 20% with the click of a button. After this initial cost reduction, the Loop data team was able to tackle more strategic cost optimization opportunities surfaced by SELECT's insights feature. SELECT's insights provided the confidence needed to make strategic warehouse sizing decisions that balanced performance and cost. Loop was able to optimize their CI/CD infrastructure to prevent developer bottlenecks while reducing costs on production workloads.

SELECT transformed Loop's cost management approach by becoming integrated into daily operational workflows. The data team established a routine of regularly checking SELECT as part of their other data platform monitoring rituals. This daily monitoring enables early identification of trends, new workloads, and potential issues before they become significant cost problems. The intuitive diagnostic flow allows easy identification of cost evolution, workload patterns, and immediate action opportunities for remediation.

SELECT's monitoring capabilities proved critical when Loop experienced a sudden $20K cost increase. The platform's automated alerting system notified the team of the cost spike and the deep visibility enabled rapid identification of the root cause and immediate resolution. The team quickly determined that one dbt view with an expensive window function was pulled into an hourly report, triggering the sudden cost increase, and were able to implement a fix accordingly.

Perhaps the most significant benefit has been SELECT's role in enabling data-driven conversations across different teams within Loop. The platform provides the quantitative foundation needed for productive discussions about resource allocation and business priorities. This quantified approach has transformed how Loop prioritizes technical work, moving optimization projects from 'nice to have' tech debt to strategic initiatives based on concrete savings opportunities. It takes something from tech debt to business critical, allowing the team to move high-impact cost optimization projects to the top of their priority list.