Basic Recommendations
Basic recommendations are a set of straightforward custom rules which act as filters. In addition, you can sort these items by numeric catalog attributes. Basic recommendations consist of the following models.
1. Item attributes
These are the catalog filters that can be sorted by some catalog attribute, such as price. These recommendations are used when you want to promote certain types of products. Additionally, these recommendations can be customized to align with the user's profile.
Example use-cases
- Reveal the 'New arrivals' section
- Inspire with your branded collection
- Celebrate with our festive picks
- Recommend ideal jobs matched to your users' skill set
- Locate local restaurants near your customers.
2. User actions
These models aid in recollecting items that users have recently engaged with. In the retail sector, when a user creates a wishlist or adds an item to their cart, it indicates their strong intention to purchase. Likewise, in classified industries, viewing an item can be seen as a strong indicator of interest. By customizing campaigns that focus on recalling these interactions, they can serve as a decisive factor.
Example use-cases
- Recover lost sales with cart abandonment reminders
- Get back-in-stock alerts and never miss out
- Boost engagement with personalized campaigns from users' wish lists
- Re-engage users with recently viewed items
- Drive repeat business with gentle nudges.