Now the industry and academia have been discussing a word, that is, big data. Whether IT is the academic circle or the IT circle, as long as you can talk about big data, it will be very tall. However, big data mining, big data analysis, big data marketing and so on are just the beginning. For most companies, big data still has a strong mystery. So before we fully understand how to use big data for mining, all kinds of public opinions that are too deified by big data have been heard. Of course, there are also many people who directly criticize the privacy threats brought by big data or big data marketing. There are also many people who simply don't understand what big data is and what value big data has.
So, from an objective point of view, I would like to share some opinions about big data with you around the following questions, and also discuss those things about big data: 1 Is there a causal and logical relationship between big data marketing and personal privacy disclosure?
2. What kind of value can big data marketing bring to enterprises? What value can it bring to users? Do users completely deny or hate big data marketing?
3. How to treat big data correctly? How to treat the relationship between big data and traditional survey methods or statistics?
4. What are the challenges of big data marketing?
First of all, the rapid development of big data is accompanied by concerns about data privacy.
The emergence of social media has made the sharing of user data reach an immeasurable level. Nowadays, there are more and more types of social media, and the greater popularity of smart phones makes more users transfer to the mobile Internet, thus further contributing more data and content. This increase in data has caused the global social media revenue to soar. According to the research results of Gartner20 12, the global social media revenue in 20 12 is expected to reach169 billion USD.
On the one hand, social media is full of big data. On the other hand, users constantly hand over personal information to the Internet without reservation, including age, gender, region, living status, attitude, whereabouts, hobbies, consumption behavior, health status and even sexual orientation. For a time, big data mining, big data analysis, big data precision marketing, and accurate advertising of massive user information were quickly put on the agenda by major companies.
For example, a true story in the United States will tell us how to use data mining to grasp our whereabouts. An American family received a promotion for pregnant women's products from a shopping mall, which was obviously for a girl at home 16 years old. The girl's father was very angry and went to the mall to discuss. But a few days later, my father found that his 16-year-old daughter was really pregnant. The reason why shopping malls are unpredictable is to predict customers' pregnancy through a large number of consumption data of several commodities.
Nowadays, similar big data mining and marketing events are more frequent, especially after social media generates a large amount of data. As a result, many people began to worry about personal privacy data and began to criticize big data precision marketing for infringing on personal privacy. They worry that we have entered an era when big data is out of control and attribute the reason to social media.
Second, big data marketing and personal privacy disclosure cannot be completely equated! Logical relationship is not established!
If we objectively analyze the above problems, we will find it difficult to distinguish whether chickens lay eggs or eggs lay chickens. It is not objective to blindly criticize the disclosure or abuse of personal user data by big data analysis.
Because the essence of social media lies in sharing and communication, the emergence of social media really satisfies people's desire to share personal information and expose all kinds of data, so that people can suddenly move to a platform and let the whole world see themselves in their silent lives in the past. People get inner satisfaction and existence from this. Therefore, from the individual's psychological consideration, social media is beneficial to them. They don't think their contribution is an ulterior secret. Since sharing, we must hope or allow others to see it. Therefore, this is an invisible tacit transaction, users are willing to expose their trivial details on social media, and there is nothing wrong with orderly sorting out and analyzing the chaotic massive user data on social media.
Of course, if social media platforms abuse or freely disclose users' background information, such as personal contact information, home address, bank and other extremely confidential information, it is indeed a naked invasion of privacy and extremely immoral, and must be condemned and punished by law.
However, at present, the premise of many precision marketing of big data is to classify and analyze the public and obvious information left by users on the Internet, so as to group a large number of users, or further subdivide minority groups, and even realize personalized customization of a single person to a certain extent, and finally achieve the purpose of accurately pushing advertisements or carrying out targeted marketing activities.
Therefore, from this perspective, there is no contradiction between the precise marketing of big data and the active sharing of information and data spread to the network by individuals. People may be surprised at first: why do they know what I want to buy? Why do they know my needs? However, with the push behavior of "guessing the heart" making people's lives more and more convenient, such as saving a lot of time to search, find and compare products or services, they may be very used to and rely on this accuracy, and will not care how the messy information they freely share on the Internet is excavated and utilized.
Therefore, whether the information published and shared by users is private or not has been carefully considered and screened before users share information. This is very important. It is the boundary between invasion of privacy and non-invasion of privacy. The information that users choose that is not suitable for publishing or that they don't want others to know is what users think is privacy, while the information that has been publicly published on social media or network is considered by users to be transmissible.
Therefore, the ordinary big data behavior of analyzing, mining and classifying massive public information for precise marketing cannot be blindly criticized as harming the interests of users. The information that users store in a specific location and don't want others to know (privately stored information), if leaked or used by people with ulterior motives, is an invasion of privacy. But this can't be blamed on big data, but should question the security of the storage platform.
Therefore, we cannot over-interpret the precise marketing of big data. In fact, the essence of the problem lies in whether people really care about the whereabouts of messy information (involving the psychology and motivation behind sharing information). And does big data marketing really touch people's hidden secrets or bottom lines (need to redefine secrets and bottom lines)? Because, if what people share by default is public, then the concept of invasion of privacy is untenable. If people have information that they don't want others to know, they won't rashly share and spread it online.
Third, what value will big data marketing bring to enterprises and users?
After discussing the above issues, should we be sincere about the precise marketing of big data? So what kind of value does big data marketing have for enterprises and users?
1, the value to the enterprise
Let's look at a foreign case first:
We all know the American drama House of Cards. When it comes to the success of House of Cards, the biggest contribution is big data analysis. Therefore, House of Cards has almost become a classic case of big data marketing, and it is also a successful attempt by Netflix to determine content production based on user information mining.
Netflix has about 30 million subscribers, and most of the movies watched by users are related to the accurate recommendation system. Netflix regularly collects and analyzes users' behaviors of watching movies or TV series. For example, it analyzes users' viewing habits according to users' ratings of movies, users' sharing behaviors, users' viewing records and other information, so as to infer what kind of TV series users like, what style they like, and what kind of directors and actors they like. On this basis, the algorithm is used to recommend and sort the videos that users are interested in until users find their favorite TV series. The director and starring role of House of Cards was predicted by Netflix after mining user information.
Then let's look at another domestic case:
We all know the cooperation between Alibaba and Sina Weibo. Alibaba invested 586 million yuan in Sina Weibo. In addition to the reasons why Alibaba, analyzed by major online media, hopes to build an ecosystem, strengthen traffic portals and challenge Tencent, another important reason may be the strategy of big data marketing.
Today, major Internet giants are encircling users. Whoever can circle users and make them active on their own platforms will have a lot of user information (including explicit foreground information and implicit background information). Sina Weibo has hundreds of millions of users in China, and its scale is huge. However, if Sina can't make rational use of the information generated by these users, these resources will be a huge waste. Let's look at Alibaba, the largest e-commerce platform in China. It has products, but there is no complete information about users' daily life behavior, only purchase information, but these purchase information is not enough to understand the characteristics and preferences of the crowd. Therefore, we have to cooperate with Sina Weibo to master a large number of users' behavior information, classify it, and find out users' preferences, preferences, interests, hobbies, habits, communication habits, sharing paths, etc. Whether different people or even different individuals can achieve accurate marketing and even formulate the best brand communication path of products through the information communication laws of different users. This is a huge gold mine.
After Sina Weibo cooperated with Alibaba, some product recommendation information appeared in Weibo, and Sina Weibo has launched the payment function. As you can imagine, in the future, if you see related recommended products on Weibo, which happen to be your favorite products, then you can directly realize payment and purchase on Weibo. So Sina Weibo and Alibaba got what they needed and enjoyed it. Of course, this is my personal observation and analysis, but Alibaba's big data strategy is also obvious.
2. Value to users
The above two examples are all about the value that big data brings to enterprises. So, is big data marketing valuable to users? Are users disgusted with precision marketing? Let's take a look at a new survey data:
The National Advertising Research Institute of Communication University of China just released the 20 14 report on the development of China-US mobile Internet, comparing the usage habits and attitudes of Chinese and American users towards mobile advertising.
According to the survey, the advertising contents that are most likely to be responded by smart terminal users are: (1) advertisements related to the items that users want to buy; (2) coupons related to the items to be purchased; (3) Funny advertisements; (4) Advertisements related to users' favorite brands; (5) Advertisements related to users' online access to websites or applications; (6) Recent online shopping related advertisements; And (7) advertisements related to the user's location. (Proportion > =20%)
From these data, we can see that six of the eight results are related to the precise marketing of big data. For example, an advertisement related to an item that a user wants to buy may cause a response or interaction from the user. How to understand? The premise of big data marketing is to calculate and guess the real needs of users, see what related products users need to buy, and then directly push what users want and like, so as to achieve accurate arrival. What about users? Users are willing to respond to this kind of promotional advertisements or products because these advertisements are less disturbing to users, reducing the decision-making process of comparison or shopping around before buying, saving time and allowing users to directly find the products or services they really need.
So this result shows that the precise marketing of big data does not make users completely disgusted, but depends on how much you can guess the user's mind. So, if the content you push is related to the items that users want to buy, related to the brands that users like, and so on. Then this kind of accurate mining will not be disgusted by users, but will bring convenience to users.
These are the things that Bian Xiao shared for you about big data. For more information, you can pay attention to Global Ivy and share more dry goods.