# User Labeling User labeling helps identify and categorize users based on their on-chain behavior, enabling more targeted and effective incentive strategies. OpenBlock Labs uses advanced analysis techniques to understand user engagement and long-term value. #### **Methodology** At a high level, OpenBlock’s user labeling methodology involves analyzing transactional patterns to profile users based on their activities, such as liquidity provision, trading, and borrowing. By examining the frequency and volume of these interactions, we can assign labels to users that reflect their commitment and involvement in the protocol. We also consider behavioral metrics like user net worth and engagement level, helping us assess the potential long-term value of each participant. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.openblocklabs.com/intelligence-models/user-labeling.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.