In the past ten years, BAT has accumulated a huge amount of data. Baidu has accumulated user search behavior, covering all aspects of life such as medical care and travel; Alibaba has accumulated relevant data of users' purchasing behavior, from decision-making to purchasing and purchasing goods, while Tencent has accumulated information of users' communication.
With basic data and scientific analysis and processing, customer value can be generated. If there is no useful data, it is "a clever woman can't cook without rice", which can't be called a veritable data website, just like you have a martial arts secret book, but you can't do it yourself, and you can't be called a martial arts master.
Public Comment has been working in the local O2O industry for more than ten years, and has accumulated more than 42 million pieces of evaluation information, more than 65.438+million pieces of business information and 65.438+08 billion pieces of user mobile data, thus improving the membership system. This is the basis for public comment to become a data website and an important milestone. In addition, public comments have accumulated a lot of data such as transactions and user browsing.
The content (that is, data) on the public comment website is generated through UGC. Data is generated from the first user uploading the first merchant, and the content generated every month is as high as one million. First, show the basic information of the business, and then more and more user comments. In this process, the platform has accumulated data of both merchants and users.
One is the data about business address, dishes, environment and services, and the other is the consumption habits of users. In the process of user comments, there is also a mechanism to constantly adjust and improve business data.
When public comments began to involve trading business, the data was more abundant. At present, in the big data structure of public comments, the user's behavior log data accounts for most of the total data, and the rest is transaction data.
Massive user comments include users' preferences for food, the geographical location of activities and even the transaction information behind them. Data are constantly being generated, which meets the basic needs of social division of labor to generate data.
At present, the applications launched by public comment are divided into two categories: one is merchant link and promotion link, which are paid products; Another kind, such as public comment index, provides consumers with decision-making; There is also a weather vane for the catering industry to provide reference for the development of the industry; At the same time, it can provide personalized recommendations for users in business; Comments on housekeepers can help businesses analyze business behavior and user characteristics. At the same time, public comment is also making an open platform, which is to open the data to third parties. On this basis, they will carry out secondary development, and openness is the trend of big data applications.
Not long ago, the public comment technology department made an interesting attempt to extract information about constellation consumption characteristics from a large number of user comments, and published the information on the Internet, which received many fans' responses. This entertaining data attempt is just the beginning, and more and deeper data exploration can be done later.
In a previous interview, Zhang Tao mentioned that a lot of information can be obtained based on the analysis of users' comments in a region and the click traffic of users. For example, in a certain city, which food is more popular and which project is more concerned. Public comment can analyze a region through big data and even turn it into the development level and stage of a business circle.
Generating millions of UGC content every month is only a milestone of public comment data. With the enrichment of user data, combined with user search, transaction and other data, public comment can provide users with more and more intelligent products.
As far as products are concerned, a steak lover will be given priority when searching for nearby delicacies. This is just a simple application. With a wealth of data, public comments can give you advice directly. Which merchant's medium-rare filet mignon suits your taste best? This information is more intelligent and intimate for users.
Of course, the mystery of the whole big data application has only been revealed a little bit, more in the concept and idea stage, and there is still a long way to go.