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How Picnic tracks in-app behavior and delivers enhanced product features with Snowplow

Using data created by Snowplow, online supermarket Picnic is optimizing the user experience by delivering helpful, personalized product recommendations.

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Background

Picnic is the world’s fastest growing online supermarket. Launched in 2015 as a mobile-first mart to make grocery shopping simple, fun and affordable, the online retailer has grown by more than 500% per year. 

Challenges

As a mobile-only supermarket, Picnic doesn’t have physical stores. Rather, their app is their storefront—so it’s critical to understand the in-app behavior of their customers. Data-driven decisions are the key success factor of this young and ambitious company. 

Picnic needed a data infrastructure designed to adapt to their fast growing business—one that could scale, evolve and deliver clear insights about each stage of the customer journey so the team could continue to deliver personalized, user-friendly experiences.

Solution

Picnic is using Snowplow to improve the customer experience. All the behavioral data created with Snowplow is stored in Picnic’s own AWS account, so they retain complete ownership—which gives them complete freedom to use the data they collect. This is the foundation of their data-driven business. 

Picnic uses the behavioral data to track app usage and understand customer behavior in as much detail as they want. Every user action within the app is collected and analyzed to determine what types of products customers prefer. What’s more, Picnic uses AI algorithms powered by data created with Snowplow to make product recommendations that are personally relevant.

Snowplow’s granular, event-level data and the ability to create custom events (e.g. adding a product recommended by Picnic to the basket) give Picnic the flexibility to: 

  • Aggregate and analyze the data that matters to their business 
  • Track in-app features in the way best-suited for analysis
  • Analyze which app features are used by different customer segments  
  • Know what products customers look at, add to their basket and buy, which can be used to manage stock (catalog analysis) 
  • Easily and quickly A/B test multiple versions of each new app feature and measure their effect on the customer experience
  • Analyze customer behavior to detect signs of churn, and use this information to proactively improve the customer journey

These analyses lead to insights that enable Picnic to optimize the in-app experience for their customers. Further, Picnic uses Snowplow’s integration with Adjust to understand where users come from when they download the Picnic app, to better measure marketing attribution and understand the customer journey.

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

DIMITAR NEDEV | DATA INFRASTRUCTURE LEAD AT PICNIC

Results

One of the greatest advantages of the Snowplow framework is its scalability. With the Picnic customer base growing at an astronomical rate, Snowplow can easily scale up to cope with the growing volume of data. It means Picnic developers and analysts can focus on new product features, rather than on data infrastructure.

What’s more, the level of detail provided by the customized in-app tracking events enables Picnic to make informed decisions faster—which further assures Picnic’s rapid growth.

How you can get started with Snowplow

To learn more about how Snowplow can empower your organization with behavioral data creation, book in a chat with our team today. Alternatively, Try Snowplow is our free, easy-to-use version of our technology, which allows you to create your own behavioral data in under 30 mins.

Ready to start creating rich, first-party data?

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