RFW0095: We need to store all the data about the monlam.ai web app usage for analysis
Named Concepts
Summary
We need to store all the data about the web app's usage so that we can analyze the usage
web app traffic
which user uses which model
Frequency of usage
We need to make the storage async so that it does not slow down the User Experience. need to look into it but if we are gonna parse the log and get all the datas
Input
User Identification Data:
Collect user IDs or session IDs to differentiate between users and their sessions.
User Interaction Data:
User inputs for each model (e.g., like id of the data stored ).
User settings or preferences selected (if applicable).
Traffic Data:
Total number of users per day/week/month.
Peak usage times.
Geographic distribution of users.
Expected Output
Usage Statistics:
Total number of uses per model.
Average duration of use per model.
Frequency of use by the same user.
User Behavior Insights:
Most popular models and features.
Patterns in usage times and durations.
Correlation between user demographics and model preference.
update terms and condition agreement accordingly to the data usage.
Expected Timeline
You need to mention the expected time line you want.
RFW0095: We need to store all the data about the monlam.ai web app usage for analysis
Named Concepts
Summary
We need to store all the data about the web app's usage so that we can analyze the usage
We need to make the storage async so that it does not slow down the User Experience. need to look into it but if we are gonna parse the log and get all the datas
Input
User Identification Data: Collect user IDs or session IDs to differentiate between users and their sessions.
User Interaction Data: User inputs for each model (e.g., like id of the data stored ). User settings or preferences selected (if applicable).
Traffic Data: Total number of users per day/week/month. Peak usage times. Geographic distribution of users.
Expected Output
Usage Statistics: Total number of uses per model. Average duration of use per model. Frequency of use by the same user.
User Behavior Insights: Most popular models and features. Patterns in usage times and durations. Correlation between user demographics and model preference.
update terms and condition agreement accordingly to the data usage.
Expected Timeline
You need to mention the expected time line you want.
References
Include all the relevent references.