The better the understanding? the more targeted the marketing This link strategy may be? and the more likely it is to produce good results. Now? for the first time? the advertising delivery system understands advertising like a human being.
For example? after learning this background information and knowledge? the big model of the 3.0 platform has a preliminary “idea” on how to help advertisers place ads. avoid the “random blindness” of ads during cold start? and directly match people who may be interested in the ads.
The so-called random blindness This link
Means that in the 2.0 era of advertising? when implementation costs will be incurred ads are cold started? some advertising systems match ads to audiences relatively randomly. Even if Party A defines the range of people according to labels? it is just a random “lucky” trial and error within this range. But in the 3.0 era of advertising? the system selects the right audience after “cognition” and “thinking”? and it is definitely not trial and error.
Of course? to achieve the above? the big model must also deepen its understanding of the crowd. It is not about building a so-called “label system”? but about dynamically and real-time grasp of data. After all? friends who do placement can understand that labels are also layer filters in arcgis field maps metaphysical? and they are mechanical and static things: sometimes? not selecting the labels of the target population? or even deselecting these labels? can even have better results. Who can you reason with?
The core is not to establish
A label system? but to truly enable the advertising delivery on adb directory the system to achieve accurate cognition. In order to achieve this? Tencent Advertising 3.0 system has deeply connected and integrated the underlying data of advertising? and used dense large model technology. The core value of this technology lies in the ability to learn from the full amount of data and parameters? so as to achieve in-depth and comprehensive cognition.
