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Recommended For You

The “Recommended for You” widget uses a shopper's browsing and product view history to suggest products that they may be interested in. Utilizing this widget, you can provide customers with personalized shopping experiences. These profiles are automatically generated, allowing you to provide precise, personalized product recommendations.

In simpler terms, the “Recommended for You” widget is a personalized shopping assistant that shows you products you're likely to be interested in based on your browsing behavior. It's most effective when placed on the homepage or on a search results page that doesn't return any results but won't show any recommendations for first-time visitors.
The Recommended for You algorithm is an AI algorithm that uses a shopper's browsing and product view history to recommend products that they may be interested in. It can be used without a graphical user interface (GUI).

How does it work?

The Recommended for You algorithm works by training an AI model on a large dataset of shopper’s behavior data. This data includes information such as what products shoppers have viewed, purchased, and clicked on. Once the model is trained, it can be used to predict which products a shopper is likely to be interested in based on their past behavior.

The following logical order would be used by the algorithm to generate RFY recommendations:

  • Collaborative
  • Content
  • Session-based

Supported Rule Types

  1. Global
  2. Home Page
  3. Product
  4. Category
  5. Cart
  6. Search

Behavior for Not Logged-in User

  1. For User’s who haven’t logged in , our system tailors the “Recommendation For You” widget based on their session activities.If the user has interacted with the products during the session the system provides recommendations derived from those viewed items.
  2. For the brand new users who haven’t explored any products yet :
    1. Fallback Disabled : Without fallback enabled, the widget remains hidden for these users
    2. Fallback Enabled : With fallback activated, the widget displays products suggested by the fallback algorithm, ensuring a meaningful engagement even for new visitors.

Behavior for Logged-in User

Systems know the user now,

  1. By utilizing collaborative, content, and session logic sequentially, the system generates “RFY” recommendations that are finely tuned to match the user’s preferences and behaviors.
  2. If the user is brand new and has not browsed any products but has just created new account and logged-in,
    1. Fallback Disabled : without fallback, the widget remains hidden when users haven’t browsed any products yet.
    2. Fallback Enabled : The widget showcase products recommended by the fallback algoirthm, ensuring a seamless experience even for freshly logged-in users.

The Recommended for You algorithm is a good choice for anyone who needs to provide personalized product recommendations. It can be used on a variety of platforms, such as e-commerce websites, mobile apps, and email marketing campaigns.

Example

Here is an example of how the Recommended for You algorithm could be used in Experro

    1. A shopper visits an e-commerce website and views a product page for a designer sofa.
    2. Experro uses the Recommended for You algorithm to predict which other products the shopper is likely to be interested in based on their browsing history.
    3. It displays a list of recommended products for the shopper on the product page.

image.pngTo create or learn more about widgets, go to our Widget Configurator article and get started.




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