"We integrated Snowplow with the Growthbook platform to give us the ability to define feature flags, run experiments, measure performance, and analyze results – all within the same ecosystem. As we increasingly incorporate experimentation in our culture, our product managers are able to set up and run experiments with minimal …

“At some point, you will reach a certain performance plateau in terms of what you can optimize if you have batch features. We were thinking, is there value for us if we get these near real-time signals into the search? That's why we started looking into solutions that we can …

“Snowplow has a lot more power and flexibility, and the thinking around event structures and event schemas is miles ahead of the industry. The Snowplow dataset has become part of our core strategic offering.”

“Snowplow has given us the power and flexibility to collect and analyze data, making smarter product decisions in ways that would be impossible with other tools.”

“The Snowplow framework has become indispensable to understanding the Picnic app usage and allowing us to focus on the most impactful features.”

"A shopper who browses products on Burberry.com is telling us something about what she really wants. Thanks to Databricks Lakehouse Platform and Snowplow, we can build an AI-Ready Customer 360 so our client advisors have that information from the moment she walks into our store — and can deliver a …

"When we attempted to integrate data from Adobe Analytics into our existing platform, we encountered significant processing and performance issues.”

“Without Snowplow data, a data-driven approach to systematically improving retention would not be possible.”

"We needed to have better control of the data to meet our requirements in terms of compliance. We really wanted to make sure we could track more efficiently—in the past, we had to limit our tracking based on what was available.”

“Snowplow’s rich, granular data enabled us to build sophisticated audience intelligence and double the efficiency of our clients’ trailer advertising campaigns.”

“Having access to the event-level data with Snowplow enables us to not only finely segment users, but also provide users with highly personalized adverts and experience.”

“We would not have achieved our current level of self-serve data without Snowplow. It has enabled us to democratize our data culture, significantly improving our analytics coverage and deepening our insights.”

“Often we think a lot about operations, observability, all the things you need to make that thing work for your specific use case but we didn’t always focus on being able to get the data to analysts, what the shape of those queries would be and what questions we would …

"Instrumenting a feature was something that was difficult and time consuming for our analysts, product engineers, and data engineers. And this limited the appetite for vertical teams to add tracking to their features. We thought that if we could reduce the complexity of event tracking, instrumentation coverage would improve dramatically.”

"With Snowplow data, we were able to measure project success through an A/B test. In our experiment, we hypothesized that our new Route Detail Page will help Strava users feel like they have enough information to take the next step with a route, resulting in increased engagement with the product.”