Big Data change retail business to step up layout industry development

2013 National Social consumer goods retail total growth rate of 13%, although maintained the growth trend, but the overall growth rate tends to slow down. In contrast to the overall online retail, the growth of 50%, although compared to the past few years, online retail speed has slowed, but still higher than the overall growth of consumer retail sales. Another set of data, we can see that in the last quarter of 2014, online retail accounted for more than 10% of the total social retail sales record high, in such a large background, the traditional entity's retail is very much impacted.

The application of data in retail tycoon emerged

First of all, from the needs of industrial development, large data can help retail enterprises to insight into consumer demand, retail enterprises in the face of changes in the market, consumer demand changes in such a large background, need to adjust to the changes in consumer demand for my strategy. And this time need large data technology to do support, in fully understand the premise of consumer demand, enterprises to redefine their value, this time also need large data to do support. The third one we see the current line under the convergence of such a trend has been very obvious, online enterprises through the electric business platform or mobile platform to develop online business, online business enterprises to carry out offline operations, the entire channel retail this model can not be separated from the support of large data. From the industrial innovation model, one is C2B, will be the original seller-oriented mode to the buyer mainly, and by the user's purchase to drive the production of enterprises, in this process requires three support system. One is the need for very personalized marketing, the second requires very flexible production, and the third requires a socialized supply chain. And these three support systems for large data requirements and large data processing put forward higher requirements, which are inseparable from a large data support.

The second is a O2O example, the line under the integration of online development This is a trend in the future, and in the O2O process will inevitably produce a lot of data, how to use the data more accurate for consumers to provide services, so that consumers quickly and accurately find the goods they want, And how to help consumers buy quality-assured goods, which require large data support. This is an opportunity for the entire retail industry to develop data.

Specifically, at present, more and more enterprises have put large data to the strategic assets such a position, from the overall size of China's large data market, this year we expect the overall growth rate should be more than 30%, is expected to 2016, the entire market will exceed the size of 10 billion yuan. From the application of the whole retail enterprise data, the application rate is less than 5%, the potential of the retail industry data is unlimited. China's big retail data is now the overall market start-up of a preliminary, large retail data from 2011 in China began to appear, immediately by the market very big attention. Here we can see as Alibaba at the end of 2011 launched the Taobao Index, to help buyers and sellers of Third-party users to analyze their product trend, or search for some hot spots, or some trends in sales data and so on. This was at the end of 2011, and China's big data at present we are judged to be the beginning of the market. Why not? Although there are many applications have appeared, but mainly within the enterprise, internal resource optimization within the enterprise, such a process, or the capital market, although very concerned about, but with large data as the core competitiveness of listed enterprises have not appeared, so we judge the next 3-5 years, China Zero The development of the sales data will still move from the exploration stage to the rapid development phase, but the time is still 3-5 years.

Let's take a look at the type of data for the entire retail industry and, by the boundaries of the business, we can divide the retail tycoon data into both internal and external data types. And from the online enterprise and offline enterprises look, in the early days of enterprise development information, in fact, the magnitude of this data, should be from megabytes to TB level, types mainly include transaction data, such as operational data, such as supply chain data, such as user data, this is the main type of retail enterprise data. After entering the large data age, the type of retail enterprise data extends from the internal enterprise to the outside of the enterprise, and this scale also develops from TB to ZB such a magnitude. The type of data is also from some of the user data, operating data, transaction data, has now been developed to the external data of some interaction, until our big data, is such a trend. And now we look at online enterprises and offline enterprises, from this map can be seen, such as shops or channels, such as some data, is a line of these attributes, is the offline category. such as traffic, conversion rate and so on, is the online retail unique data attributes. This is the type of data for the entire retail tycoon.

China Retail industry Data trends

1th, the cross series, China's retail enterprises online under the coordinated development or integration development is a trend in the future. How to use large data to achieve line offline Enterprise Cross series analysis, this is a big data future need to study a direction.

The second is value derivative, which can be understood as how to achieve full application of large data, there are two directions, one is the online enterprise, the direction of the enterprise is to develop their entire platform into a data product, such as Alibaba first he is a platform, and he has his own technology research and development, derived from becoming a data product, This product includes both platform data products and later Cross-border financial-related products. Offline business practices, if there are many years of accumulation of these traditional retail enterprises, the practice is that I can open up my data resources, such as gome to open their supply chain data, through the data sharing with strategic partners to maximize data value.

The third is decision making, which can be understood as using large data to help make decisions better. Through the analysis of data, we can draw a result of the decision, usually, the big data analysis of the decision results will be unexpected. However, the results of this data analysis is not based on policy makers or leaders for the transfer, through the data analysis to come to these conclusions, we again serve the qualitative business texture of some analysis, comprehensive make our decision.
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