The “Pick-up where you left off” recommendation algorithm is designed to enhance user experience by suggesting content or products that aligns with the users past interactions on the platform.
It ensures a seamless and personalized journey, enabling users to effortlessly exact point they last left, increasing overall user satisfaction.
How does it work?
This algorithm functions by tracking and analyzing a user’s historical interactions with content. It captures the user;s engagement history, such as viewed media, products or pages. When the user returns the algorithm recommends content based on their past interactions from exactly where they keft off so that they can seamlessly resume their shopping experience.
Supported Rule Types
- Home Page
- Category
- Product
- Cart
- Search
When should you use this algorithm?
Use this algorithm when you want to enhance the user experience by providing personalized recommendations based on their historical interactions. This algorithm is well-suited for content-heavy platforms, such as new websites, streaming services, or e-commerce sites, where users frequently explore various items and may benefit from the seamless continuation of their journey.
Example
Here is an example of how the Pick-up Where You Left Off algorithm could be used in Experro
- A shopper visits an e-commerce website and views a product page for a designer chair.
- Experro uses the Pick-up Where You Left Off algorithm, which pays attention to your purchase history and ratings.
- The algorithm recommends designer chairs that other people with similar tastes like.
- It displays a list of products that are recommended by the algorithm for the shopper on the product page.
To create or learn more about widgets, go to our Widget Configurator article and get started.