48 Snowplow Testimonials

“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.”

"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 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.”

“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 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.”

"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 new asks and challenges.”

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

"Before Snowplow, we had Google Analytics 360 and our behavioral data was not available in real time in our Snowflake warehouse or in our AWS infrastructure. Snowplow opens up a world of possibilities for us because we can provide data to our team to analyze trends in campaigns to analyze what’s happening within five or 10 minutes.”

“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 use that don't require us to rebuild the whole infrastructure for ourselves. Because we are aware that this is quite cumbersome. And it takes quite some engineering effort to get this into a production stable state.”

“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.”