Strava sets the pace with self-serve data

Using Snowplow Behavioral Data Platform, Strava’s analysts can easily access massive volumes of rich, granular data.

4 billion events collected and processed per day

Analyst and product teams self-serve the data they need

More time for data engineers to focus on innovation


Strava is the world’s most popular platform for athletes to record and share sporting activities. Once dubbed ‘the social network for athletes’, it is now home to 64 million active users in over 195 countries.

With 3 to 4 billion events collected every day, Strava’s relatively small data team was struggling under the weight of terabytes of data. Analysts couldn’t self-serve the data they wanted without support from engineers, and it was proving difficult to implement tracking for new features.

The team sought a cost-effective way to ‘democratize’ Strava’s data to make it readily available to analysts, while simplifying the process of adding tracking new product features. Both would help Strava create a culture of continuous product optimization.


Using Snowplow Data Platform, Strava has streamlined data collection and enabled self-serve access to data at great scale—without incurring huge costs. Data analysts can easily define custom events and entities, and can also instrument end-to-end tracking themselves.


Strava is using Snowplow’s robust data infrastructure to capture behavioral data at scale directly in their Snowflake account.


A consistent approach to tracking ensures analytics forms part of the product lifecycle.

Managed infrastructure

With Snowplow handling data creation, Strava’s data team is free to focus on core projects.


Snowplow Behavioral Data Platform has proven more cost-effective than hiring one or more full-time engineers to manage Strava’s data pipeline. More importantly, it means that Strava’s small data engineering team can focus their resources on more meaningful analytics projects.

Looking ahead, Strava plans to use Snowplow to deliver real-time data to power use cases for the machine learning and product teams. For now, though, the team knows that Snowplow’s large-scale, enterprise data platform helps keep Strava at the top of its game.

Read Strava’s full story


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