Personalizing recommendations
A recommendation system is an application that recommends products to users based on their buying and search preferences. This aspect is not limited to just product placement but is also used in medical diagnostics and treatment. For example, recommendations may help with understanding how patients respond to medication and what kind of treatment sequence is more effective.
As the data grows and the number of products available increases, the ability to understand user behavior and provide the most personal recommendations becomes more and more important.
These strategies can be used to build personalized experiences. Some of these strategies are mentioned here:
- Building user profiles: We can build custom user profiles by understanding user behavior. Behavior patterns can include the order of transactions made by users for a given time period or outcomes of events that occurred, along with other attributes such as age, race, and gender...
