48 Snowplow Testimonials

“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.”

“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 can massage it into something that is very easily communicable to all of our feature developers and product managers.”

"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 present it in our all-hands meetings.”

“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.”

“With Snowplow, we are empowered to make more informed, data-driven decisions that allow us to iterate much faster while gaining a multi-dimensional view of the user experience now and in the future.”

“Our reliance on Snowplow data is increasing, using it for reporting, for in-depth insights and to answer more complex questions. Snowplow lets us elevate our reporting and our business to the next level.”

"We needed something better than Google Analytics because we weren’t gaining meaningful insights and building a complete customer picture with the tool.”

“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 be asking of that data, and are we going to be able to provide the answers.”

"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.”

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