Recommendation Usage

Relewise supports a large number of different recommendation types, each one keyed to deliver different results for different use cases. In order to get the most out of your Relewise recommendations, it is useful to understand the context within which each recommendation functions best. The outline provided below seeks to offer an immediate overview of the most common use cases and examples. For a more precise walkthrough of the various recommendation types, refer to the recommendation types page

Increase Basket Size

Recommendations to increase the size of a customer's basket are designed to help guide the user towards more directly relevant products, based on their previous behavior and the behavior of customers with similar tastes.

Recommendations to Increase Basket Size
Popular Products	Displays popular products, based on the number of purchases and/or views within a given time period, and is ideally placed at the top of the funnel to serve as inspiration to the user.
Personal Product	Shows products directly relevant to the user's tracked behavior. This helps invite attention to products that might be directly relevant to the user's interests.
Purchased With Multiple Products	Helps with upselling on the cart page by showing relevant products based on current cart contents. By showing products that have been recorded as being purchased together, odds are that the user will find something relevant.
Similar Products	Helps guide users towards products similar to the one they are viewing, on the basis of concrete product information. Rather than relying on tracked user behavior, this lets users access products that are fundamentally similar, on the basis of traits such as size, color, material, brand, etc.

Increase Conversion Rate

Increasing your conversion rate means helping more of your customers find the product(s) that will encourage them to commit to a purchase from your store. These recommendations are designed to serve up products that are more likely to be of relevance to the ambivalent buyer, to ensure that they move through the funnel all the way to the order confirmation.

Recommendations to Increase Conversion Rate
Popular Products	Displays popular products based on the number of purchases and/or views within a given time period, and is ideally placed at the top of the funnel to serve as inspiration to the user.
Personal Product	Shows products directly relevant to the user's tracked behavior. This encourages users to engage with products that are likely to be more relevant to them, and leads to greater conversion rates.
Products Viewed After Viewing Product	By directing the user from a current product towards other products that other users have shown interest in, it helps drive engagement and heightens the likelihood that the product will be of interest to the user.

Increase Customer Loyalty

The most successful customer experience is the one that gives the customer the urge to return at a later date, and/or recommend your service to their peers. These recommendations aim to tailor the shopping experience for your users, and invite them to return over and over again, with better recommendation results every time.

Recommendations to Increase Customer Loyalty
Personal Product	Shows products directly relevant to the user's tracked behavior. This encourages users to engage with products that are likely to be more relevant to them, and encourages user interest and retention.
Similar Products	Helps guide users towards products similar to the one they are viewing on the basis of product information. Rather than relying on tracked user behavior, this lets users access products that are fundamentally similar, on the basis of traits such as size, color, material, brand, etc.

Reduce Bounce Rate

Before the sale can happen, it is important to catch the user's attention and ensure that they are sufficiently interested in the products on offer. These recommendations help reduce the bounce rate of users, and prime them for a sale.

Recommendations to Reduce Bounce Rate
Popular Products	Displays popular products, based on the number of purchases and/or views within a given time period, and is ideally placed at the top of the funnel to serve as inspiration to the user.
Products Viewed After Viewing Product	By directing the user from a current product towards other products that other users have shown interest in, it helps drive engagement and heightens the likelihood that the product will be of interest to the user.

Recommendations by Location

In order to help find the best recommendation type for your use case, we have collected a few suggestions for useful locations and situations that may serve as inspiration during implementation.

For contextual matching of recommendations to a certain scenario, we have created a page of recommendation usage.

For more location-specific use cases, refer to the following table:

Location	Recommended Request Type	Description
Front Page	PopularProducts	Shows the most popular products for a given time period, based on most views and most purchases.
Product Details Page	ProductsViewedAfterProduct	Increase conversion rate by showing products that other users have navigated to after not putting the current one in the basket.
Product Details Page	PurchasedWithProduct	Increase basket sizes by showing other products often purchased together with the current one.
Cart/Basket	PurchasedWithMultipleProducts	Shows products purchased with the products currently added to the basket.
Power Step	PurchasedWithProduct	Increase basket sizes by showing other products often purchased together with the current one.

Content Recommendations

For sites where content plays a large role, recommendations can help users navigate organically between articles and promote relevant content according to other users' preference. In particular, the PopularContents recommendation type is useful for promoting the articles that have recently proven popular among your userbase - just remember to define the SinceMinutesAgo value.

Similarly, the ContentsViewedAfterViewingContent recommendation type helps connect users to other articles that are similar and related to the subject that they are already viewing. This can also be combined with users' product interest by employing the ContentsViewedAfterViewingProduct recommendation, which can help guide users towards relevant articles for, e.g., how to use the product in good or creative ways.