“Snowplow provides all of our event data in a data model we own end-to-end, and can easily shape to fit our organisational needs. Snowplow has really helped accelerate our analytics; now we can quickly answer questions that would have required a tremendous amount of engineering effort with our previous solution.”

“Snowplow has been helping us centralize our data and build the single customer view since day one. As we get closer to pinpointing precisely, for example, the booking value of a particular segment, and more complex data analysis, Snowplow will continue to be what we need.”

"With data you solve marketing, advertising, and editorial questions you improve your digital products."

“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.”

"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.”

“PEBMED’s data evolution is growing more sophisticated, thanks to Snowplow. We can see using Snowplow for everything from content recommendations to tracking internal applications and APIs to better, more granular joining up of data from individual users.”

“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.”

“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 …

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

“Having Snowplow helps the business. For sales, it can be an increase in revenue because of the audience we are able to provide; for marketing, better insight into users and how they can become more engaged.”

"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.”