The media is "big data", how to explore the potential of large data?

Source: Internet
Author: User
Keywords Large data media excavation

  

Here is a number, probably not common to everyone: million 5 or 10,000 trillion, that is 1,000,000,000,000,000,000 (1 behind 18 0). IBM has estimated the concept of 10,000 trillion, that is, the amount of new data produced by humans every day is 25,000 trillion. In contrast, five of the Earth's oceans of sea water is 3.52 million trillion gallons, if a byte of data equivalent to a bucket of water, it takes only 5 months or so the "water" can fill the entire five oceans.

For businesses, it really feels powerless to face and manage these myriad of data. Oracle reported last June that 93% of the 300 U.S. and Canadian companies lost some profitable opportunities because they could not handle the data around them.

The chief marketing officer of a "big Data" Company, Pete Elliott, can help large and small businesses from huge volumes of data (such as blogs, Twitter, http://www.aliyun.com/zixun/aggregation/1560.html "> Find available information in Facebook's praise, links, images, videos, comments, text files, replies, and even container manifests. Elliott said that the more data, the faster the search speed, the more customers like.

First we need to sort out a concept: Big data doesn't mean big business. Data analysis is the way to bring profits and increase profits. Whether large or small enterprises need to remain competitive in the market, this requires a large number of data to do the corresponding market, competitive analysis, because competitors are likely to do this type of data analysis. Although it is said that 25,000 trillion of data are produced every day, it is meaningless if the information is not collated and can not be used and understood properly. However, with the development of computer technology, programmers have developed more efficient software, which can help enterprises to better collect, select and organize, and finally transform the data into the analysis of the future development, and become the favorable condition for enterprise competition.

Yuchun Lee, vice president of Enterprise Marketing Management at IBM, advises companies to start large data analysis from the corporate web site. "As long as someone logs on to the site, there is an opportunity to use big data," he said. "For E-commerce Enterprises, corporate Web site is a marketing tool." Elliott also said, "The use of large data is best to start with a simple, slowly test, and eventually expand the scope of application." ”

Steve McKee, chairman of the McKee Wallwork Cleveland Company, recently made a large data service that has exceeded the site's traffic. We tracked the customer's media consumption time, web browsing, customer inquiries, purchased the corresponding data, and finally found the relationship between the above. We also tracked the ups and downs of advertising after people bought products. Using the results of large data analysis to help McKee Wallwork Cleveland customers improve media investment efficiency, it is expected to increase by 9% in 2013.

Data also has a very important impact on consumer satisfaction. Ryan Hollenbeck, senior marketing vice president of Verint Bae, told the story of a consumer calling the Customer service Center for questioning. The customer discovers that the advertisement of the enterprise is misleading (unintentional). Another customer, using voice analysis, found that customers wanted to cancel their accounts in a customer conversation, and they judged the potential customers by keyword and key sentences, and the enterprise customer saved more than 600 risk customers through large data analysis, avoiding 12 million of dollars in losses.

Perhaps the most exciting part of the big data is helping companies predict the future. Many police stations use historical data to predict when and where crime can occur, and companies use consumer online behavioral data to develop the products they want. For marketers, social media has previously been a place where businesses interact with customers in real time, and now they have big data that can dig deeper into consumer information, improving products and discovering consumer demand. "There may be a great potential for further development in social media conversations," Hollenbeck said. How to explore the potential of large data? Enterprises need to do is to try large data services, a glimpse of it can be brought about by the company's general progress. Elliott said that complex data analysis based on cloud services could be very inexpensive in the future, as low as 1000 dollars/times. Ten years ago, when people were doing business face-to-face, businesses had to deal with customers from a very narrow perspective. Today, casual conversations on the web can become a prerequisite for product trading. If enterprises still do not agree with large data, see the relationship between large data and consumers, still can not use large data, it is likely to lose a valuable opportunity.

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