Accurate ranking of Google ads remarketing advertisers six times in half a year

In the field of Internet search, advertising rankings have always been the focus of attention of the industry and users. On August 26th, Google Global R&D Director Miao Xiaohu conducted a system for the development of Google advertising products and the R&D technology behind it. A comprehensive introduction.

“Our ad ranking depends on a professional data analysis system, which depends on both the ad quality score and the maximum cost-per-click (CPC).” Miao Xiaohu told reporters that Google’s ad’s score was determined by the ad’s clickthrough rate, ad text relevance, and ad’s history. Performance and other relevant factors depend, and the maximum CPC is determined by "the advertiser's highest price for each click," thereby achieving a fair, fair, and comprehensive ranking system.

Looking back at the history of Google’s advertising system, Google’s initial advertising system was born in 1999. Since then, Google AdWords (Google Keyword Advertising), Google AdSense (Google Advertising Alliance) and other advertising products have appeared. Today, Google has created a huge, Strong, successful advertising business model, as of the second quarter of this year, in the past four quarters, Google's total revenue from advertising over 30 billion US dollars.

According to Hu Xiaohu, Google's advertising products experienced three major transitions in 2002: from pay-per-view development to pay-per-click; the introduction of an auction system and the use of second-price sealed auctions; the introduction of a quality scoring system that uses quality scores to encourage high-quality advertising. .

Since then, the Google advertising system has successfully solved the technical challenges of massive data and user access, high stability, rapid synchronization of dynamic data, high computational complexity, and low response time, supported by three major technical systems. These three major systems include storage systems, machine learning systems, and matching systems. Among them, the storage system can store massive advertisement data, statistical data, and log records and guarantee rapid indexing and real-time updating; the machine learning system performs event analysis, behavior analysis, correlation learning, concept extraction, garbage filtering, etc.; matching system realizes complex The auction process can satisfy a large number of users simultaneously accessing, guaranteeing high stability and low response time.

Google's innovation is obvious to all. In the field of Internet advertising, display advertising is an important product in the Google advertising system. Advertisers can not only choose to display their own products, enhance their interactive experience with users, stimulate their desire to purchase, and get more targeted customers.

In display advertising, what attracts attention is the Remarketing product, which can help advertisers reach users who have visited their websites. Its rapid development in China, the number of advertisers using remarketing has been in 6 It increased by 6 times in the month.

For example, Dunhuang.com has used remarketing products and achieved good results. According to the analysis of Internet users, online shopping usually goes through four stages of “know, understand, compare, and purchase”. Dunhuang.com focuses on the integration of customers' purchasing process when it conducts display network and search advertising marketing. They found that 10% to 15% of the customers would be lost after the display network was in the first three stages of the purchase process. They did not form a purchase at Dunhuang.com. After using Google remarketing, the customer turnover rate decreased from the previous 10%-15% to less than 5%. Currently, monthly remarketing orders can achieve a 30% increase.

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