Once the user opens the online store, how should the system work to provide their first recommendation? Cases to consider include:
No user information available (new user):
- In the case of a new user, the system might provide general recommendations based on popular items or trending products.
Insufficient user information (user with little history):
- For users with limited history, the system could rely on initial interactions and preferences to make tailored suggestions.
Other considerations to keep in mind include how to avoid recommendation bias, meaning that recommendations shouldn't always come from a specific cluster.
Also, it's essential to think about how user information will be stored to build their history.
Once the user opens the online store, how should the system work to provide their first recommendation? Cases to consider include:
No user information available (new user):
Insufficient user information (user with little history):
Other considerations to keep in mind include how to avoid recommendation bias, meaning that recommendations shouldn't always come from a specific cluster.
Also, it's essential to think about how user information will be stored to build their history.