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bofrost* is a German company founded in 1966 and is a European market leader in direct sales of ice cream and frozen food specialties. The company has 5,500 vans delivering frozen goods in 12 European countries, supplying around four million households. bofrost* has been able to gain this position by offering customers a high level of product quality and customer service. The company is known for its high level of customer interaction and is now looking to evolve its business model to meet the growing global market for frozen foods.
bofrost*, a European market leader in direct distribution of frozen food, was looking to evolve its business model to keep up with the growing global market for frozen foods, projected to reach $282.50 billion by 2023. The company's IT infrastructure relied heavily on legacy systems, with two on-premises data centers in Germany and Italy. Information about products was provided to customers via a twice-yearly print catalog, and salespeople used a basic device to access details about orders to be delivered. However, they couldn't access multichannel order histories and other additional information. The company wanted to transform its IT infrastructure to enable new ways of meeting its customers' needs, including a new point of sale (POS) platform to streamline delivery schedules and provide personalized suggestions to facilitate upselling opportunities.
bofrost* partnered with adesso to design and build a new POS infrastructure based on Google Kubernetes Engine, Cloud Storage, and Cloud Functions. The new system is always online, providing salespeople with the latest information on customer interactions and product recommendations. The company replaced its old POS device and separate navigation device with a single touchscreen tablet, which also serves as a multichannel communication point. The tablet can be used to take online orders, handle customer service over the phone, or via messaging services. The back end, hosted on Google Cloud, powers an Android app on the tablet, which is how salespeople access the system. The company also plans to use machine learning to offer personalized recommendations and optimize the daily schedule for its salespeople.
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