With the development of network technology, netizens enjoy the convenience brought by the Internet, but the rapid development of the Internet has also brought them the problem of information explosion. How to quickly mine information that is effective for netizens and has marketing significance for enterprises from these huge information data has become an urgent problem to be solved, so the concept of network precision marketing came into being. The use of personalized technology (such as website recommendation system) helps users filter out the information they need from the excessive information on the Internet to achieve the purpose of precision marketing. E-commerce websites, media information websites, and communities have gradually introduced the means of personalized recommendation on the site to carry out precision marketing.
In the final analysis, Internet precision marketing is achieved through personalized technology. The following lists some of the development history of personalized precision marketing on the Internet.
In 1999, Tanja Joerding of Dresden University of Technology in Germany developed the personalized e-commerce prototype system TELLIM.
In 2000, Kurt and others from NEC Research Institute added personalized recommendation function to the search engine CiteSeer.
In 2001, Gediminas Adoavicius and Alexander Tuzhilin of New York University developed a user modeling system for personalized e-commerce websites.
In 2001, IBM added personalized functions to its e-commerce platform Websphere to facilitate merchants to develop personalized e-commerce websites.
In 2003, Google pioneered the AdWords profit model, providing relevant advertisements based on the keywords searched by users. The click-through rate of AdWords is very high and it is the main source of Google’s advertising revenue.
Starting in March 2007, Google added personalized elements to AdWords. Not only does it focus on the keywords of a single search, but it also records and analyzes the user’s recent search history, thereby understanding the user’s preferences and needs and presenting relevant advertising content more accurately.
In 2007, Yahoo launched the SmartAds advertising program. Yahoo has a large amount of user information, such as the user’s gender, age, income level, geographic location, and lifestyle, and the records of user search and browsing behavior, which enables Yahoo to present personalized banner ads to users.
In 2009, 0verstock (a famous online retailer in the United States) began to use the personalized banner advertising solution produced by ChoiceStream to place product advertisements on some high-traffic websites. 0verstock achieved amazing results in the early stage of running this personalized banner advertising. The company said: “The click-through rate of the advertisement is twice as high as before, and the accompanying sales growth is as high as 20% to 30%.”
In July 2009, the first personalized recommendation system research team in China, Baifendian Company, was established. The team focuses on personalized recommendations and personalized precision marketing solutions for e-commerce. On its personalized recommendation engine technology and data platform, it has brought together more than 100 well-known e-commerce websites and information websites at home and abroad, and provides real-time intelligent product recommendations to tens of millions of consumers every day through these B2C websites.
In September 2011, at the Baidu World Conference 2011, Robin Li listed the recommendation engine as an important strategic planning and development direction for the future Internet, along with cloud computing and search engines. Baidu’s new homepage will gradually achieve personalization, intelligently recommending users’ favorite websites and frequently used apps, and achieve precision marketing services.