“Kaiser’s" was a traditional German supermarket chain that had more than 550 stores in three regions spread across Germany. The company history of Kaiser’s dates back to the 1880s. In the 1970s it was one of the biggest grocery retailers in Germany, but at the end of 2016 it was sold to Edeka and Rewe, the two largest grocery groups in Germany.
Digitization and demographic changes in society were working against traditional offline grocery retail
At some point Kaiser’s had trouble catching up with other grocery chains that were using new technologies and embracing the blurring line between online and offline retail. Kaiser’s also offered its product range at prices that were on average 10% higher than at other supermarket chains, which meant it faced challenges in terms of price perception. Also, the demographic changes in German society left Kaiser’s (as well as all other grocers) with fewer young customers, who tended to shop at discount chains such as Aldi and Lidl.
Anonymous loyalty card with individually optimized discounts applied in real-time
SO1 approached Kaiser’s with a convincing idea in 2014, namely, to apply individual promotional offers in real-time to Kaiser’s customers via a new loyalty program, one that would reduce effort and costs to a minimum while delivering maximum output and profit. This new solution, called "SO1 Optimized Discounts", had three USPs.
First, SO1 would provide individual discounts. Customers received 8 individualized promotional offers by scanning the loyalty card at a kiosk system at the entrance of the store. Each participating user showed the loyalty card at the till and instantaneously received monetary discounts on the promoted products.
Second, SO1’s solution would maintain customer anonymity, which was new to the market. Thanks to the loyalty card being anonymous, a complex registration process, which can be expensive and lengthy for both consumers and the provider of a loyalty card, was avoided.
Third, the solution would include real-time till integration. This allowed SO1’s AI to analyze baskets, and calculate and apply the personalized promotions, which were thus kept up-to-date with changing customer preferences and external factors.
Significant increase in customer satisfaction, while saving on promotional spendings
After a successful pilot, the system was rolled out to all 160 stores in the Berlin region. After the pilot, Kaiser’s CEO Dr. Hendrik Haenecke said:
“In addition to the very positive development of revenue in participating stores, SO1 allowed us to leverage individual objectives within our promotion channel.”
The concept of personalized discounts in combination with an anonymous loyalty card was a novelty in offline grocery retail in Germany and a driver of revenue growth for Kaiser’s. It led to a revenue uplift of 1-3% across stores, confirmed by the controlling department of Kaiser’s via an A/B test. The redemption rate achieved was roughly 50%, with savings of 47% on promotional spendings. The solution was well accepted, easy to scale, and fully automated.
5 years of system improvements and fundamental research for an even better solution
Kaiser’s was SO1’s first client. Within the last 5 years, SO1 has not only added more clients to its list, but has continuously worked on improving its AI and pursued fundamental scientific research in cooperation with Humboldt University Berlin, ETH Zurich and MIT in Boston.
Today, the SO1 Engine is able to adapt to multiple communication channels, such as apps, checkout-printers, websites or any other consumer-facing communication channel a retailer might use. The impact SO1 can generate has also grown – one of the latest cooperating retailers has seen an 8-fold higher redemption rate while saving 60% on promotional expenditures in comparison to the existing solution at that retailer.
PS: SO1 is one of the driving forces of retailer digitalization. We have created a very powerful AI for retail which is capable of personalizing promotions for users in real-time and across devices. The SO1 Engine sources the entire portfolio of the retailer and automatically selects the right products for each individual consumer and adjusts discounts such that revenue, profit, or consumer satisfaction are maximized. To learn more, reach out to:
US Sales: Patricia A. Cucinelli, firstname.lastname@example.org, +1 917 757 6221
EU Sales: Stephan Visarius, email@example.com, +49 160 93 59 69 95