The best data collection platform to grow your mobile app.
Snowplow’s best-in-class data collection infrastructure is the foundation for leading mobile apps’ data strategies.
Explore your users’ in-app behavior in astonishing detail.
Snowplow events are extremely rich, each one collected comes with additional contexts such as session, screen and location, as well as fully custom contexts, allowing for a very robust understanding of your users and their behavior. Make use of your underlying data to identify and encourage the behaviors that drive your users to subscribe and continuously optimize on your in-app user experience.
Correctly measure, attribute and optimize your user acquisition.
Accurately track users who go on to subscribe to your service or make in-app purchases, so you can optimize your marketing to focus on the campaigns that drive the most valuable users. Snowplow allows you to track ad impressions and understand which campaign drove users to your mobile web landing page. Tie this campaign data to in-app user engagement to build the attribution model most applicable to your business.
Decrease user churn with better predictive models.
Snowplow data is validated up-front in the pipeline and highly structured in tidy tables in your data warehouse. This makes Snowplow data a great input for your machine learning models - less time is wasted cleaning your data sets! Use your underlying data to better understand when and how likely a user is to churn by feeding your models with rich, granular event data.
Measure the impact of new app features on user behavior.
Make use of Snowplow’s rich, custom tracking to drive your product roadmap and understand how users engage with new features. Conduct A/B tests with multiple versions of each new feature, in real-time, to measure their effect on user experience and behavior so only the most impactful features go live.
A technology partner both your Devs and Data Team will love.
Snowplow’s mobile SDKs come with best-in-market auto-tracking and are built with performance in mind they batch and compress events taking battery usage and payload size into account. They even allow you to track events that occur offline using local caching. With Snowplow’s schema’ing technology there’s a single source of truth for your events - no more back and forth between your data team and developers or trying to manage naming conventions in spreadsheets.
Leading mobile apps choose Snowplow
“Snowplow has revolutionised decision making at Lifecake. We are more attuned to our user base than ever before, and the bespoke real-time tracking allows us to quickly gauge the effect of new features and releases. In short, Snowplow has changed the game!”
Data Scientist at Lifecake
From the Snowplow blog
Conducting an A/B test is more complicated than just randomly assigning users into groups. To run a meaningful experiment requires meticulous planning around what experiment is run, what the expected impact of the experiment will be, and what metrics will best capture that impact. It is essential that the process of running the tests, measuring the results, and making the decision whether or not to roll out each product update is as frictionless as possible.
Lifecake, a service for family members to collect, share, and celebrate memories, wants to use data to make sure that they’re improving the service for their users, while growing their user base, over time. They were spending a lot on acquiring new customers, but their user base wasn’t growing as fast as they were expecting. After the first round of analysis on their product data, a retention analysis showed that a huge percentage of users dropped Lifecake after day one.
We released new versions of the Snowplow iOS and Android SDKs. These new versions deliver a data set that is significantly easier to model and work with: helping companies use mobile data to better inform product development and marketing decisions. In this post, we’ll explain how the data delivered by these new mobile trackers is both easier to work with and better enables analysts, data scientists, marketers and product managers to do more with that data.