Large data analysis: Retailer "holiday sales" secret weapon

In Western countries, "black Friday" and "Network Monday" (the first Monday after Thanksgiving) are used to denote two major holiday shopping events of the year. But many people may not know that these two dates are not just dates on the calendar, but also the time for many retailers to start laying out big promotions, which actually determine the overall profit level of the year.

Therefore, from the two major festivals to the New Year holiday, this period of operation for the entire retail enterprise annual sales bottom line is very important, won the 2012 "Thanksgiving Day" retailer, the use of secret weapons is "large data analysis."

So what is the role of big data in the retail market? Web sites, GPS-enabled tablet devices and smartphones, embedded sensors, increasingly using mobile communications technology, generate a lot of consumer behavior data.

This is the first time both technically and economically, to store and analyze these consumer data and to discover all feasible new insights and marketing patterns. Savvy retailers are collecting and digging up big data from targeted customers at a more personalized and direct level, especially on important holiday needs.

What is the effect of this year on the use of large data by retailers? Data from Google Analytics show that large data can deal with a wide range of activities, including effective marketing activities, can be targeted at customers online purchase behavior, their preferences for sales and promotion, to achieve social E-commerce and inventory optimization.

For example, large data analysis may enable retailers to conduct direct-related promotions and marketing activities, motivate consumers to buy online and track the resulting sales transactions. At the same time, large data as a result, retailers can monitor and real-time adjustment of promotional activities, to maximize consumption, improve profitability, in the critical period of a short period of time to generate maximum benefits.

This is done by quickly cutting terabytes of data, including daily millions of emails, every click on the site, and information on each e-commerce transaction. These advanced analytical methods enable retailers to carry out in-depth, accurate customer segmentation statistics, such as age, income, interest, lifestyle profiles, psychological pursuits, and so on to optimize and develop personalized promotional activities.

Time-sensitive data analysis needs to promote the "self-service" large data analysis trend of the rise. Data analysis can answer their own business problems, large data sources in minutes, without the need to wait weeks or months, so that the market has long been changed, wrong judgment, missed business opportunities.

Now, the IT department is offering retailers too little data and too late. This has prompted retailers to use the latest and most cost-effective large data platforms, such as Hadoop, which is powerful. A successful example of large data analysis is beachmint, an online seller of haute couture jewelry, apparel and footwear.

BeachMint is a very smart social-electronic website that can track all of the data, including every time we click on the network and through every sales transaction in its email marketing.

Large data analysis, changed the traditional buyer and seller game rules, because the retailer can now easily analyze user consumption, seize effective cross-selling opportunities, using advanced referral engine, to motivate buyers to spend. It can be said that the biggest winners of this year's "holiday promotion" are those who have staked their bets on using large data analysis to optimize their revenue.

(Responsible editor: The good of the Legacy)