Online retail case study

How Picnic uses Snowplow to deliver users with a smart, data-driven shopping experience

Picnic is a unique company. The world's fastest growing online supermarket that makes grocery shopping simple, fun and affordable for everyone. They now reach more than 800,000 people and continue to grow exponentially. Their motto is: Think, Dare, Do.

“The Snowplow framework has become an important data analytics tool, indispensable in understanding the Picnic app usage and allowing us to focus on the most impactful features”.

Dimitar Nedev, Data Infrastructure Lead

Picnic launched in 2015 and they quickly won several prestigious awards: 2015 Challenger award, 2016 Best startup award, 2017 Most innovative company award. They started as a mobile-first venture and are now transitioning to an AI-first company, where all innovations and operations are powered by their machine learning core engine.

Providing a smart, personalised shopping experience

Picnic uses Snowplow to track user's experience and engagement with their shopping app. They use the data to drive and validate product development decisions (e.g. using A/B testing) and merchandising decisions. As well as being used for offline analytics, the Snowplow data is used operationally: powering AI algorithms to determine what products to surface in the app.

“Together with the level of detail the customised in-app tracking events provide, Picnic can make informed decisions faster, knowing that our in-app analytics system will be able to handle the Picnic growth”

Dimitar Nedev, Data Infrastructure Lead

A scalable framework that supports explosive business growth

The Picnic customer base has grown more than 5 times in 2016 and the number of orders in 2017 has already surpassed (in May) those for the whole 2016. As the Snowplow framework is designed to scale up easily, Picnic has been able to easily adapt to the growing data volume, without service interruption.

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