Data-Driven Shelf Management for Red Bull

Saving up to 80% on Time

AI product recognition streamlines data collection for sales representatives.

Improving Shelf Product Display Seamlessly

The app guides immediate adjustments to product layouts.

Increasing Accuracy and Compliance

Red Bull secures price and layout coverage across hundreds of stores.

"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

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 345+ stores, under the brands of Globus and Albert (which belong to the portfolio of Ahold).

The 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.

The Challenge

When we started our cooperation, the data on market shelf share lacked accuracy. Information regarding sales volumes and product pricing in the energy drink category was costly and partially based on assumptions. The collection of such data was manual, increasing the overall expenses for merchandisers. These merchandisers had other tasks of higher value to perform during their visits; therefore, manually counting products led to significant inaccuracies, and there was an absence of price comparison.

The Solution

To address these challenges, we implemented our product, Shelf Inspector. This app is adept at monitoring shelf layout and capturing relevant information through photos taken in-store. We have fine-tuned Shelf Inspector to achieve nearly 99% accuracy in recognizing Red Bull cans. The process of shelf management starts with data collection using our app, which sales representatives or merchandisers utilize to take images. These images are subsequently processed through a suite of neural networks in the cloud. The system identifies shelves, products, and price tags and aligns them with the planogram. All statistical data, including photographs from visits, are stored and accessible on a dashboard for management review. Although this solution can be adapted for all hyper-scalers, it was specifically tailored for Red Bull using Microsoft Azure and Databricks technologies.

The Benefits

The benefits of incorporating the Shelf Inspector tool for Red Bull have been significant. The tool has streamlined the data collection for sales representatives, cutting down the time required by up to 80%, according to an internal study. This means they can get their work done faster and spend more time on other important tasks. The app also makes it easier to adjust product layouts on the shelf right away, keeping displays organized without delay. Furthermore, Red Bull has seen an increase in the accuracy of their pricing and the consistency of product arrangement in stores, ensuring that customers see what they expect wherever they shop.

Need to Know More?

Ask us anything

Key contacts

Andrej Bodi - DataSentics

Andrej Bodi

Retail Project Delivery