If you buy a coffee maker in a home appliance business, you will continue to see advertisements for coffee makers. However, you do not need to buy one. The good data should be that after you finish the transaction, you are advertising coffee beans or electric coffee makers.
General manager insights and solutions Google Greater China and South Korea in the area Guo Zhiming T112016 cum TalkigData Intelligent Data Summit, to share with you how Google will link all data sources, into the practical application of insight into the brand, as well as to boost advertising Marketing experience for big data marketing.
Guo Zhiming said that Google's big data marketing practice experience is mainly divided into three parts:
Discover insights from the data;
According to consumer behavior, interacting at multiple contact points;
Measure real KPIs.
| How to find insights in the data
There are three main sources of Google data integration:
First-party data is data owned by the company itself. Google launched Google Analytics 360, a global data solution, in March this year. Through the products in this program, users can access the official website of the customer, or use the interactive behaviors and interactions of the users of the customer app.
The second party data is customer relationship management (CRM) data. Google will pass the collected CRM data to different vendors and platform management. To make the data better connected, Google has developed the Double Click Data Platform to exchange data that is associated with customers at any time.
Third-party data is data obtained from supply.
Based on Google’s own experience, Guo Zhiming believes that there are three major challenges in the application of big data.
False traffic and data can lead to erroneous budgets and conclusions;
Dispersing incomplete data leads to incomplete and in-depth understanding of user needs;
Data silos result in decentralized applications.
For these issues, Google has its own principles and methods of handling.
First, establish an anti-spoofing system to combat policies, sort out fraudulent traffic and defraud clicks, and establish trust relationships with customers. In the fraud system, technology is the core. Guo Zhiming gave an example. If it is the same APP, the range of charts for real people clicks has a regular distribution and spreads in the center of the chart. The range of icons clicked by the robot is distributed, random and relatively balanced.
Second, connect the data to achieve the whole process of linking users and brands.
Third, we must pay attention to data security and encrypt all API layers.
| How to interact and interconnect data
Although Google's search platform, Google through its own search management platform Double Click Search and Baidu connection API, manage Baidu's SAM. Guo Zhiming told Lei Feng Network (search "Lei Feng Network" public concern) , Google has a lot of Google Analytics as the core platform to connect the customer's data. In addition, Google will monitor the exposure of the ads to track where the clicks occurred, whether it was in the station, on the PC, or on the mobile phone.
By monitoring all consumer behaviors, Google can better understand consumers. For example, if you want to know the identity of a person searching for a place of travel, you can tell by his consumer behavior whether he is a business traveler, a family traveler, or a honeymooner. Google hopes to interact at multiple touchpoints based on consumer behavior, whether across data search, video, or display, across screens and across situations.
| How To Measure Real KPIs
Guo Zhiming gave an example with Cristiano Ronaldo. Ronaldo scored on the court, but his credit was not alone. Advertising marketing is also the same, although most people are still accustomed to the marketing effect attributed to the last click, but no brand exposure is impossible to generate clicks. Google now uses machine learning to use data-driven attribution models to calculate the role played by each marketing segment.
Guo Zhiming said that based on the return on investment (ROI), the advantages of this attribution method over traditional attribution methods can be clearly seen. Google also has different KPI measurement tools for different customer groups. For intelligent data, Guo Zhiming believes that big data is not outdated, and smart data generated by machine learning still depends on the results of data.
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