Future retail analysis needs retailers to support customer insight with integrated business processes and information systems, and develop customer insight into an enterprise-level strategic capability, which is rooted in enterprise structure and culture. In this case, all business functions of retailers will take customer insight based on scenarios as an important basis for decision-making.
EKN, an analysis company, believes that in order to be truly customer-centric, retailers need to have many key capabilities, all of which are driven by business analysis.
All-round integration. Without relevant customer insight to support the interaction with customers, retailers will not be able to achieve a seamless cross-channel customer experience. The contact points between retailers and customers can provide retailers with rich customer data, so all the contact points have become the best competitive weapons for retailers.
Personalized interaction. Compared with online retailers, physical retailers have two advantages: personal contact with customers, richer historical records and more diversified customer data. Nowadays, "personalized" shopping experience has become a hot topic, and how to combine the above two advantages skillfully, that is, to convey customer insight in time in action, will become the basis for retailers to create a "personalized" shopping experience.
Continuous operational excellence. The application of customer insight is not limited to customer-oriented use cases. In fact, if retailers have been able to use analysis functions more maturely in various operational functions, integrating customer insight is an incremental opportunity that they can't miss.
Retailer use case
sell
Globus, a Swiss retailer, uses big data memory computing and advanced analysis to gain valuable insights into sales performance. At present, they can process massive product data in real time and analyze the sales patterns and promotion activities of thousands of products in different time ranges, stores and regions in a few minutes. The retailer also provides these insights to its managers so that they can react to market conditions more quickly.
Guess, an American retailer, uses advanced analysis to provide its executives with a real-time view of best-selling products and available inventory. The retailer's analytical solution is based on large customer data sets, analyzing sales, segmenting target customers and planning promotional activities.
marketing management
Wal-Mart's Global.com department makes full use of "fast big data" and social analysis to quickly identify changing customer preferences. The retailer's Social Sense project can determine the best-selling degree of goods through social media, and help customers explore potential demand and interested new products. At the same time, with the help of ShoppyCat tools, they can recommend suitable products for Facebook users according to their hobbies and interests. In addition, Global.com also uses social genome technology to help customers choose gifts for their friends.
The target department store uses the predictive analysis program to infer whether individual consumers have the characteristics of becoming quality customers of the company's specific marketing activities. They assigned each customer a unique customer identification number. This number integrates the customer's personal information, shopping behavior and preferences into a traceable entity. Target has also set up a special customer marketing analysis department, which is committed to fully understanding customers, surpassing other competitors and gaining a competitive advantage. With the help of active data warehouse, Target can manage complex user queries based on massive data in the mixed workload environment of the whole enterprise.
Omnidirectional
British retailer Burberry integrates all its channels, including physical stores, online stores, mobile terminals and major social networking sites. They use innovative technology and data analysis to analyze data from all data sources, aiming at identifying individual customers in real time and establishing customer files. Compared with the past, the analysis speed of Burberry has increased by1.4000 times. It used to take five hours to request, but now it can be completed in 1 sec. No matter where the clerk is, as soon as they step into the store, they can immediately identify the customer information, understand their past purchase records and provide personalized advice.
South Korean retailer NS Shopping integrates mobile channels and social channels into the retail environment, and uses big data analysis to obtain real-time and centralized customer and product data of all channels. The company's e-commerce team and marketing team will use these data to provide personalized product suggestions to customers.
supply chain
Amazon, an American online retailer, has built a brand-new supply chain process and system based on non-stationary stochastic model. This method can provide strong support for order fulfillment, procurement, capacity and inventory decision. Amazon has not only developed a new algorithm for joint and coordinated replenishment, but also implemented a brand-new national forecasting scheme at SKU level based on historical demand, activity records and plans, forecast results of fulfillment centers, inventory plans, procurement cycles and purchase orders.
Tesco, a British retailer, uses advanced modeling tools to simulate the operation of distribution warehouses according to historical sales data, thus achieving the purpose of optimizing inventory. Retailers also set up an internal analysis team, which is mainly responsible for mastering the relationship between various elements through regression testing, such as weather data, special products, sales models and so on.
The above are eight typical cases that Bian Xiao shared for you, to understand the "big data" strategy of retail giants. For more information, you can pay attention to the global ivy and share more dry goods.