User Profiling: Development Process and Applications in Data Intelligence

With the end of traffic dividends and rising acquisition costs, companies have entered a stage of refined user operation, where user profiling becomes crucial.

User profiling involves labeling users' habits, behaviors, and attributes to create a comprehensive view that supports advertising recommendation, content distribution, and marketing, forming the foundation of big‑data technologies such as computational advertising, personalized recommendation, and intelligent marketing.

Since raw behavior data cannot be directly used for analysis or model training, labeling transforms behavior logs into understandable information for both humans and machines, enabling personalized recommendation, personalized search, precise ad targeting, and intelligent marketing.

Image source: Internet

The development process of user profiling includes the following steps:

Design the tag taxonomy.

Confirm data sources.

Collect data.

Validate data.

Produce tags.

Deploy tags.

Provide tag services.

Image source: "Data Intelligence Knowledge Map"

For more user‑profiling content, readers are encouraged to follow the associated public account and download the full "Data Intelligence Knowledge Map".

Additional AI knowledge sections in the map include intelligent risk control, recommendation systems, pre‑training, privacy‑preserving computation, A/B testing, and causal inference.

References:

"After reading this, you won’t claim you don’t understand user profiling" – https://zhuanlan.zhihu.com/p/28485415

"Finally, someone explained the user profiling process and methods clearly" – https://www.51cto.com/article/669421.html