For example, a sports brand is very interested in Xiao Ming’s cross-screen behavior. If traditional marketing techniques are used, at best, one can only observe that his browsing behavior on different devices is divided into broad categories such as: sports, technology, finance and travel. Because there are so many touch points (various behaviors)), it is difficult for brands to determine whether other people are also using these devices, not to mention these large-scale interest topics are still not precise enough to piece together Xiao Ming's "single customer profile" ”.

Artificial intelligence can analyze Xiao Ming's cross-screen behavior and the keywords he has browsed in the consumer journey, subdivide sub-categories within the large category, and link the devices he owns together to determine Xiao Ming's online behavior. Keywords such as "Basketball Virtual Reality Game", "Bitcoin", and "Cheap B&B" appeared many times in the articles I read while traveling around the world. Therefore, when a sports brand wants to market to him, it can tailor its marketing materials (basketball shoes, star co-branded models) and contact channels based on Xiao Ming’s comprehensive insights, and further develop a relationship with Xiao Ming (and those who have the same interests as Xiao Ming). The interaction between them generates more brand connections.