Feature management platform LaunchDarkly has announced the acquisition of Houseware, a pioneer in warehouse-native product analytics.
In addition, the company also announced the private preview of Warehouse Native Experimentation, its Snowflake Native App, to offer Data Warehouse Native Experimentation.
Together, these initiatives enable LaunchDarkly to deliver experimentation designed for engineering teams and loved by product teams, while providing AI-powered analytics for deeper insights into how customers engage with products.
Today, engineering, product, and data teams want to centralize their source of performance metrics into a single data warehouse. While centralized data is critical, these teams also want to democratize data-driven decision-making and experimentation. Currently in private preview, LaunchDarkly is leveraging the Snowflake Native App framework to integrate its advanced experimentation capabilities within the robust Snowflake data environment, enhancing data governance, scalability, and flexibility. By centralizing data sources and experimentation analysis, this collaboration empowers teams to generate deeper and more actionable insights, accelerating and improving product development cycles.
Key solutions offered through the Snowflake Native App:
- Data Seamlessly Available in Snowflake: Data engineers, scientists, analysts, and product managers often face challenges in conducting sophisticated analyses due to data being siloed across tools. With custom warehouse analysis, users can leverage advanced targeting and assignment capabilities in the LaunchDarkly Snowflake Native App. They can then seamlessly export the results back into their Snowflake table for downstream analytics, using their preferred data tools and workflows to enhance decision-making processes.
- Warehouse Native Experimentation: Users frequently lack a unified platform to design, run, and analyze experiments with enriched warehouse data. Warehouse Native Experimentation is a Snowflake Native App that centralizes comprehensive experimentation data inside customers’ Snowflake accounts. This Snowflake Native App streamlines metric creation and results visualization, making it easier for teams to conduct and analyze experiments alongside data in their environment, fostering quicker and smarter business decisions.
“With organizations looking to make a greater business impact through new features, it’s now more crucial than ever to not only control these feature releases but also to measure and experiment with them to determine the best ROI,” says Dan Rogers, CEO of LaunchDarkly. “Our integration with Snowflake, combined with the product analytics expertise brought by our acquisition of Houseware, elevates our ability to deliver actionable insights and transform software delivery practices for engineering, product and data teams alike.”
“Working with LaunchDarkly enhances both companies’ commitment to empowering businesses through data-driven decision-making to drive innovation forward,” said Kieran Kennedy, Global Head, AI Data Cloud Products at Snowflake. “By developing a Snowflake Native App, LaunchDarkly is on a path to making advanced experimentation and analysis more accessible to a wider range of teams, enabling smarter, faster business decisions.”
The acquisition of Houseware is a major step toward unifying experimentation and analytics within a single platform. Houseware’s warehouse-native, no-code solution sits on top of Snowflake, enabling developers, product, and data teams to integrate analytics into their daily workflows and tools. By monitoring critical release metrics in real-time and measuring feature impact against key business objectives, teams can ensure scalable, reproducible experiments while confidently making data-driven decisions.
