The Similar Products Recommendation algorithm suggests items closely related to a given product, enhancing the user experience by providing alternatives or complementary options based on shared characteristics, features, or user preferences. This algorithm analyzes product similarities to offer personalized and relevant suggestions, fostering increased engagement and potential conversions.
How does it work?
The algorithm gathers information about what users look at and buy. It studies this data to find similarities and patterns among products. The system uses patterns and similarities to suggest related products to the user. The algorithm can find similarities between products by using different factors, like category, price, and brand.
Supported Rule Types
- Global
- Home Page
- Product
- Cart
Recommended Placements
- Product Page (SP) for this product
- Cart: SP for products in the cart
- Checkout: SP for products being purchased
When should you use this algorithm?
Use the Similar Products Recommendation algorithm in CMS when aiming to enhance user engagement and offer personalized suggestions based on shared characteristics. This algorithm is well-suited for platforms where showcasing alternative or complementary options to a given product can improve the overall user experience, such as e-commerce websites, retail platforms, and content-driven sites with a focus on user personalization.
Example
Here is an example of how the Similar Products 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 Similar Products algorithm to recommend designer chairs or fancy chairs using the customer's online preferences. We can give you a personalized recommendation. It will help you find the perfect designer chair. It will also make your shopping experience more satisfying.
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It displays a list of Similar products for the shopper on the product page.
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