Data competition: Business intelligence applications in American retailing

What is the biggest feature of retail industry in the United States today? Network？ Internationalization？ None of them. In early January this year, the New York Times reported that the biggest feature was the data explosion. You can probably imagine the data and calculations needed to detonate an atomic bomb or send a rocket, which is based on high, fine, sharp calculations over massive amounts of data, but this amount of data and computing methods are becoming commonplace for retail giants such as Wal-Mart and Amazon.

The reason why the data is "exploding" is that the data collection consciousness and information integration ability of the major retailers have been greatly improved in recent years. For example, the application of radio frequency technology (RFID) in retailing not only improves the granularity of data acquisition, but also enhances the real-time and accuracy of the information, and greatly promotes the growth of data volume in the retail industry. The New York Times says the number of individual retailers has even increased 5 times-fold over the past 3 years because of changing attitudes and the adoption of new technologies. This data is becoming the retailer's biggest asset and resource. Among them, the point "number" Gold's wand, is the business intelligence analysis software.

Careful inspection will find that business intelligence in the retail field "Shinton", has not been a department or local phenomenon, but penetrate the entire industry, in-depth application of bone marrow. Today, every cell in the retail industry can be said to be breathing in the "intelligent Analysis and prediction" air.

The first is customer analysis. Every product that flows into the hands of a customer will produce a record at the front of the sales desk, analyzing these data, we can grasp the structure of customer group, cycle flow and profit contribution rate of different customer groups. Each customer can determine the frequency of their purchase and predict their interest in goods, loyalty and wastage trends. With these analysis from the point of point, it is possible to predict the consumers ' willingness to consume, offer personalized sales and promotion services to customers, and increase sales and profitability.

The second is commodity analysis. The core question is how to determine the best portfolio and inventory for each branch, when to import new products, and eliminate old products. How to classify the existing goods on the shelves, and what goods to put together, or bundled sales? What is the price of each item, when it is lowered, and in what form, after the festival, during the off-season season, even in the morning and evening? For example, a hurricane will be landing in Florida next month, the bottled water, rain gear and other related goods should immediately increase the amount of storage, and what goods to improve? How much more? These are all based on data analysis to answer good questions. Individual analysis requires not only internal data, but also data from external sources such as market, industry research and peer competitors.

Once again, the analysis of the supply chain, the analysis of operational efficiency, including the selection of suppliers, optimize logistics and cash flow, the allocation of human resources, selection of store locations and so on.

These analyses are interlocking and integrated. For example, if you import a new product that doesn't sell well, stranded shelves, supermarkets may become a "museum", even if the supply chain and operational efficiency is again high, but also an empty; For example, the shortage of individual goods, if not enough inventory or supply chain lag, the shelves will be vacant, missed business opportunities do not say, also wasted space.

Lin Lin all sorts of things. In a word, data analysis based on a variety of dimensions has been the norm in retailing, and these analyses have laid the foundation for a wide variety of business decisions. It is no exaggeration to say that the competition in the retail industry has become a competitive part of data collection, integration and analysis, and the ability to integrate and analyze data is becoming the core competitiveness of retailers.

At present, the data-centric competition is still white-hot, more high-end business intelligence applications are beginning to emerge in the retail industry.

This is mainly manifested in two aspects. One is the application of mobile business intelligence. The US at&t phone company has been working with Vaultus software to launch a retail business intelligence mobile program, and a group of US retailers such as A&p, AVON, TJX, Inc., have been able to browse the dial report on their phones. Recently, one of the giants of business intelligence, MicroStrategy, also announced their mobile business intelligence solutions. The second is to extract the customers ' opinions through the text analysis. The consumer experiences of customers in blogs, forums, social networking sites and Twitter, and their perceptions and evaluations of consumer behavior and commodities are unstructured data. It is also one of the hot topics of business intelligence to integrate the unstructured text resources distributed on the network and excavate valuable information for the retailer.

Regardless of the history, or inspection of the status quo, the retail industry is still not sitting on the business intelligence applications of the "head of the top", the front seat is also the financial, financial, insurance and other fields. The full application of business intelligence in retail industry tell us, industry data explosion will affect the industry's future competition, the future of the competition will be more refined, this refinement, reflected in the data analysis, many industries, have to enter a data hing Enterprise Hing, data strong enterprise strong data competition era, in this era , the data is the direct wealth, is the core competitiveness.

For this kind of data competition, every industry and enterprise in China should be prepared.