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We Must Understand The 10 Major Breakthrough Points Of Big Data Marketing.

2014/8/17 21:31:00 33

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Data Marketing Breakthrough Point Understand

many people are less than a href= "http://sjfzxm.com/news/index_c.asp" > feeling /a > to the age of big data is coming, but it is often just a hazy feeling, and the power of its true marketing can be described in a fashionable word -- unaware. 
 first, user behavior and feature analysis. Obviously, as long as we accumulate enough user data, we can analyze users' preferences and purchase habits, and even achieve "better understanding of users than users". With this, it is the premise and starting point of many big data marketing. In any case, those companies that used to "take customer as the center" as slogans in the past can think about the fact that in the past, you really could understand the needs and thoughts of customers in a timely and comprehensive way. Perhaps only in the era of big data can the answer be more clear. 
 Second, precision marketing information push support. Over the past few years, precision marketing has always been mentioned by many companies, but little is done, instead of spam. The main reason is that in the past, nominal precision marketing was not very precise because it lacked user characteristics, data support and detailed and accurate analysis. Relatively speaking, the application of RTB advertising shows us better accuracy than before, and behind it is big data support. 
 Third, guiding products and marketing activities to users. If you can understand the main characteristics of potential customers and their expectations for products before the production of products, you can do well in your product production. For example, Netflix has known the potential audience's favorite directors and actors before the recent film house, through the analysis of big data. For example, after the launch of the "trailer", the small time has learned that the main audience of the movie is 90 after the big data analysis from micro-blog. Therefore, the follow-up marketing activities are mainly aimed at these people. 
 Fourth, competitor monitoring and brand communication. What competitors are doing is what many companies want to know, even though they will not tell you, but you can learn from big data monitoring and analysis. The validity of brand communication can also be identified through big data analysis. For example, it can carry out trend analysis, content analysis, interactive user analysis, positive and negative sentiment classification, word-of-mouth category analysis, product attribute distribution, etc., and can monitor the competitive situation of competitors through monitoring, and can refer to industry benchmarking user planning, according to user voice planning content, and even evaluate the operation effect of micro-blog matrix. 
 < a href= > http://sjfzxm.com/news/index_c.asp > fifth < /a > brand crisis monitoring and management support. In the new media age, the brand crisis has made many enterprises turn pale. However, big data can give enterprises insight in advance. In the process of crisis, what we need most is to track the trend of crisis communication, identify important participants and facilitate quick response. Big data can collect negative definition content, timely start crisis tracking and alarm, according to the analysis of crowd social attributes, cluster the views in the process of events, identify key people and communication paths, and then protect the reputation of enterprises and products, seize the source and key nodes, and deal with crises quickly and effectively. 
 sixth, the selection of key customers. Many entrepreneurs are entangled in: what are the most valuable users among the users, friends and fans of the company? With big data, perhaps all of this can be more supported by facts. Users can visit different websites to determine whether their recent concerns are related to your business. From the various content and interaction content that users publish on social media, you can find thousands of information and use some rules to relate and integrate them, so that you can help enterprises screen key target users. 
 seventh, big data is used to improve user experience. To improve the user experience, the key is to really understand the users and the situation of the products you use, and make the most timely reminder. For example, in the age of big data, maybe the car you are driving can save your life ahead of schedule. As long as the vehicle running information is collected through sensors all over the car, early warning to you or 4S shop will be made before your vehicle's key components have problems, which will not only save money, but also help protect your life. In fact, the UPS express company in the US used this predictive analysis system based on big data in 2000 to test the real-time status of the 60000 vehicles in the United States so as to carry out defensive repairs in time. 
 eighth, SCRM customer level management support. Facing the ever-changing new media, many enterprises want to spanform fans into potential users by analyzing the open contents and interactive records of fans, activate the value of social assets, and portray potential users with multiple dimensions. Big data can analyze interactive content of active fans, set various rules of consumers' portrait, associate potential users with membership data, associate potential users and customer service data, and select target groups for precise marketing, so that traditional customer relationship management can be combined with socialized data, enrich users' labels of different dimensions, and dynamically update consumer life cycle data, so as to keep information fresh and effective. 
 ninth, discover new market and new trend. Based on the analysis and prediction of big data, it is a great support for entrepreneurs to provide insight into new markets and grasp the trend of economic development. For example, Alibaba discovered the arrival of the international financial crisis from a large number of spanaction data. For example, in the 2012 presidential election of the United States, the David Rothschild of the Microsoft Research Institute used the big data model to accurately predict the results of the election in 50 regions of the 51 selected constituencies of the 50 states and the Columbia SAR, with an accuracy of more than 98%. After that, he also predicted the ownership of the eighty-fifth Oscar awards through big data analysis. Besides the best director, all the other awards were hit. 
 tenth, support for market forecast and decision analysis. The support of data on market forecasting and decision analysis has been put forward in the past in the age of data analysis and data mining. WAL-MART's famous "beer and diaper" case is the masterpiece of that time. Just because of the big data era, the above Volume (large scale) and Variety (multiple types) put forward new requirements for data analysis and data mining. More comprehensive and timely data will provide better support for market forecasting and decision analysis. You know, specious or wrong, outdated data is a disaster for policy makers.