"With GA, you didn’t know when you’d get your data – it could be 3 or 5 hours. You just didn’t know. Even with 360, you didn’t have everything in minutes.”

“With Snowplow data we can show a customer that 95% of actions taken during a video happen between 0:30 and 0:35 seconds. The customer can then learn what works, what doesn’t, and make the needed changes to drive significant increases in KPIs.”

“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.”

"Auto Trader loves open source technologies. Snowplow is an open source technology—we didn’t see the value of managing it ourselves, but we like the fact that we can contribute code.”

“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 use Snowplow for analytics. We build dashboards, tracking, and we also have a data catalog. With Snowplow, we are able to collect data on subscriptions, passive and active engagement. I look at the data daily and share insights with the entire organization about what’s working and what’s not, and …

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

“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.”

“With Data Connect, we’re strengthening our partnerships by sharing valuable customer insights. When airlines see the insights we can provide about their customers’ behavior on our platform, they recognize the added value we bring to the relationship.”

"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.”

"With the move to virtual events we had to provide other layers of analytics. Our organizers were suddenly interested in session view duration and attendee engagement. Sponsors began monetizing the visits they had to their virtual booths. Transforming to the digital era we were now living in came with many …