Datadog Announces "Datadog Experiments" to Connect All Product Changes to Business Outcomes
Datadog has launched "Datadog Experiments," a new platform enabling developers to design, run, and measure product experiments and A/B tests directly on Datadog. This innovation aims to link product changes to business outcomes by providing crucial data and insights.
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- 📰 Published: April 9, 2026 at 20:00
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New York – Leading AI-powered observability and security platform company Datadog, Inc. (NASDAQ: DDOG) announced today that Datadog Experiments is now generally available to customers worldwide. The new Datadog Experiments product enables developers to design, run, and measure product experiments and A/B tests directly on the Datadog platform, providing the data and insights needed to understand how any change impacts user behavior, application performance, and business outcomes.
Modern product teams rely on experimentation to validate new features and optimize user experiences. However, current experimentation tools are fragmented from business data systems, forcing developers to cobble together multiple solutions: product analytics vendors, standalone experiment platforms, and monitoring tools. This results in fragmented workflows and a lack of visibility between product changes and application performance. This gap is only becoming more pronounced as AI accelerates the pace of feature development and release.
According to Yibin Lee, Chief Product Officer at Datadog, "The faster engineering organizations release, the higher the cost of not knowing what’s working. When signals are scattered across fragmented tools, we make decisions based on incomplete information, missing the drivers that actually contribute to revenue and forfeiting bold initiatives that move the business forward."
Datadog is solving this challenge with the first experimentation platform that combines business metrics from customer data warehouses with product analytics events and application observability. Built on top of Eppo, which Datadog acquired in 2025, Datadog Experiments combines state-of-the-art statistical methods with real-time observability guardrails, enabling companies to validate key points, make decisions rapidly, and ship with confidence. This product will be used by every product manager, designer, and engine
Modern product teams rely on experimentation to validate new features and optimize user experiences. However, current experimentation tools are fragmented from business data systems, forcing developers to cobble together multiple solutions: product analytics vendors, standalone experiment platforms, and monitoring tools. This results in fragmented workflows and a lack of visibility between product changes and application performance. This gap is only becoming more pronounced as AI accelerates the pace of feature development and release.
According to Yibin Lee, Chief Product Officer at Datadog, "The faster engineering organizations release, the higher the cost of not knowing what’s working. When signals are scattered across fragmented tools, we make decisions based on incomplete information, missing the drivers that actually contribute to revenue and forfeiting bold initiatives that move the business forward."
Datadog is solving this challenge with the first experimentation platform that combines business metrics from customer data warehouses with product analytics events and application observability. Built on top of Eppo, which Datadog acquired in 2025, Datadog Experiments combines state-of-the-art statistical methods with real-time observability guardrails, enabling companies to validate key points, make decisions rapidly, and ship with confidence. This product will be used by every product manager, designer, and engine