Data-driven shelf management for RedBull

Product recognition saves up to 80% of the market data collection time

AI navigates users to immediately fix layouts

In long term, layout compliance increased and Red Bull finally has coverage of prices across hundreds of store

"With the application, our merchandisers have more time left for more important tasks […] As the main benefit for the future, we see, in addition to saving time, also streamlining work, respectively price monitoring, where we can set various alerts in case the price of a particular product falls or rises above a certain limit."

Petra Diamond

Lead of the marketing store

About the client

Red Bull is an Austrian company best known for its energy drink. The company has become famous for its marketing campaigns, often involving sponsoring extreme sports events and athletes.

Making sure that the shelves are filled with just the correct goods and that the warehouse is not overstocked is a logistical challenge, especially for big companies such as the producer of energy drinks Red Bull. Since 2018, when our cooperation with Red Bull started, we have rolled out our product Shelf Inspector solution in 15 supermarkets operated under the Globus brand and over 300 stores that belong to 330 stores branded Albert, which belong to the portfolio of Ahold. Our solution helps brands master the layout of specific goods on the shelves faster and with higher accuracy. All you have to do is take a picture.

Business use cases

Competitive Pricing - Red Bull was curious how their products, which are generally considered high-end, are priced compared to the competition when it comes to price/volume ratio.

Shelf Share – Thanks to the Shelf Inspector’s ability to recognize all products in the picture, Red Bull now has real-time coverage of what their shelf shares is in all stores of all format.

Planogram Compliance – The overall layout of Red Bull fridges and other secondary placements is key to the success. Products are sorted based on popularity and can design to impress the customer. For this reason, immediate recommendations for the staff to fix the layout were a great help.


There were no exact data about shelf share available on the market. The information about sales volumes and pricing of products in the energy drinks category was expensive and based on assumptions.

The collection of such data was performed manually, which increased the total costs for merchandisers, who also have other tasks with higher added value to perform during the visit. When they counted products, it led to high inaccuracy. There was a complete absence of price comparison.

Our solution

Shelf Inspector reaches 99% accuracy in product recognition and is constantly improving. Shelf Inspector helped brands coordinate the layout of specific goods on the shelves faster and more accurately so that the stock levels of various products are balanced. All you have to do is take a picture of the stand or shelf in the store with a mobile phone. It all starts with our own app to collect pictures. Then, they are processed with a set of neural networks in the cloud. Shelves, products and price tags are identified and compared with the planogram in a few seconds. All statistical data from visits, including photos, are stored and displayed in a dashboard. While the solution can run on all hyper scalers, for Red Bull specifically, it was based on Microsoft Azure and Databricks technologies.

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Key contacts

David Vopelka - DataSentics

David Vopelka

FinTech lead | AI & personalisation expert

Bob Hroch - DataSentics

Bob Hroch

Business Development