Rapid and profound disruption is impacting the retail industry. The uncertainty, speed, and frequency of unpredictable events, such as the COVID-19 outbreak, are prompting retailers to re-assess their operating environment, suffer higher costs due to enhanced safety precautions for both staff and customers, increase home delivery services, and improve agility in response to market requirements.
While retailers may have adopted digital platforms to enable e-commerce, the rationale and imperative for a true, omnichannel-enabled customer experience has never been more apparent. New technologies, agile competitors, as well as new, demanding shopper expectations are transforming the market. Now more than ever, retailers need a better understanding of consumer needs and a willingness to recognize, embrace, and become a catalyst for change.
So how can you not only survive disruption but harness it for growth? We’ll illustrate through customer stories 3 ways retailers are leveraging Oracle Autonomous Database to do so.
Dou Yue’s 30 restaurants across China are committed to serving traditional Chinese cuisine on premises and for takeout. Faced with intense competition, especially from caterers and internet-based food service providers, improving their ability to analyze data to support marketing, sales, finance, purchasing, and customer service was key. However, Dou Yue’s multiple, isolated legacy data platforms prevented the company from gaining the comprehensive, real-time insights it needed.
By deploying Oracle Autonomous Data Warehouse and Oracle Analytics Cloud on Oracle Cloud Infrastructure, Dou Yue integrated the data from multiple business systems onto a single, cloud-based platform. The financial team can now pull revenue, inventory, and other data, by restaurant, for company executives to act on. For example, when a restaurant posts a revenue decline, Dou Yue execs can analyze the environmental conditions (traffic, weather), sales model (dine-in or takeout), as well as menu and pricing in the region where the restaurant is located to determine the root causes and adjust strategy. By analyzing historical trends, repeat-consumption, and other data, Dou Yue is now able to understand which dishes customers like and adjust them, or create new ones, in a timely manner. They can additionally determine which commercial buildings tend to order the most take-out to inform targeted marketing campaigns and where to locate future restaurants.
Autonomous Data Warehouse is the only complete solution that uses a converged database providing built-in support for multimodel data and multiple workloads such as analytical SQL, machine learning, graph, and spatial. It requires no integration with other services, making it easy to load any data, run complex queries across multiple data types, build sophisticated analytical models, visualize information, deliver dashboards, and develop data-driven applications.
Dou Yue is certainly not an isolated case. For instance, Hong-Kong based Maxim’s is a leading food and beverage company operating 1,700 outlets throughout Asia, including quick service restaurants, bakery shops and more. It is also the licensee of renowned brands including Starbucks Coffee, Genki Sushi and The Cheesecake Factory.
They rely on Oracle Autonomous Data Warehouse and Oracle Analytics Cloud to collect and analyze 600,000 transactions per day, combined with ERP, external demographic, and social media data. Using this solution, they have gained real-time insights into customers’ buying behavior and purchasing habits to alter menus and dishes as preferences change. The results have improved marketing promotions, operational efficiency, and site selection for further growth expansion.
Autonomous Data Warehouse eliminates virtually all the complexities of operating a data warehouse - automating provisioning, configuring, securing, tuning, scaling, patching, backing up and more - enabling Maxim’s to accelerate time to insights while reducing costs and improving security.
“Our catering group manages over 70 brands with support from Oracle Autonomous Data Warehouse for efficient analysis of sales data and customer preferences, which ultimately improves our overall competitiveness. Its self-driving, self-patching capabilities provided costs savings and improved data security.” says Maxim’s Caterers Ltd’s Chief Financial Officer Keith Siu.2. Improve inventory management
It takes a lot to get a perfectly ripe fruit into the hands of a customer. With its fast-growing business and perishable products, Shenzhen Pagoda relies on data to get its fruits to the right store at the right time, taking into account each store’s preferences and consumption patterns. Managing and analyzing all that data is a massive job, and the company needed a data warehouse solution backed by automation and intelligent data management that would help it make fast decisions. It also needed a solution that would greatly reduce costs and its IT team’s involvement. “To keep satisfaction high, we want to continuously supply differentiated and personalized fruit products for customers in different stores,” says Shenzhen Pagoda’s CMO Shen Xin.