"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.”

“The gist is that once you have all the relevant data for each event, which is possible with Snowplow, you can do whatever you want with it. Snowplow’s importance will only continue to grow as we customize our pipeline.”

"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 …

“We had plenty of data already before Snowplow was introduced, but that data was mostly coming from our game servers. What we did not have was the data from the client side. And, even more importantly, we didn't have any data from various websites that we had.”

“Snowplow has been crucial for Supercell. It gives us deep insights into how players engage with our games and events. This has empowered our teams to build better experiences, especially for Brawl Stars, while driving more collaboration and aligning us closer to our community. It’s been a game-changer for understanding …

"Snowplow has been integral to HeyJobs’ growth, powering marketing attribution, product experimentation, and CRM optimization. The platform’s flexibility and Snowplow’s support team have been invaluable as we scale to become Europe’s top talent platform.”

"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 …

"The model tells us which users we should target for WhatsApp.”

“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.”

“It was especially important for us to calculate conversion rates accurately for our clients, so they could compare us to other job boards. This wasn’t possible before Snowplow.”

"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.”

“We couldn't combine our in-house tracking data with other types of information, like who made the request, what did they do, where did they come from, had they been on the site before, or if they were a member.”

“The versatility [of Snowplow] allows us to take the raw data, model it, transform it, expand it, enrich it, and come out the other end with a data set that's flexible for all of our product teams. It's highly targeted information. But through that enriching process, data stitching, identities, we …