Articles on: Recommendation rules

Learn About Different Product Recommendation Types

Plans: All Plans Platforms: Shopify


Overview


AfterShip Personalization allows you to choose from 11 product recommendation types to improve your sales figures. Check this guide to learn about all of them.


Algorithm

Description

Store Data Used

Time frame for data accumulation

User Case

Manual selection

Recommends specific products that merchants want to upsell or cross-sell through manual selection.

None

Best sellers

Recommends products that have sold the most based on all historical orders in the store.

Store orders data

30 days

New arrivals

Recommends products that are new on the shelf.

Products meta information

Frequently bought together

Recommends products that are most likely purchased together based on store order history statistics. This works well with bundle upselling.

Store orders data

180 days

Potato chips and soft drinks

Complements

Complements offer a subtle way to tie a whole look or function together with the main products, enhancing the customer shopping experience.

Store user orders, products meta information

180 days

Phone case for a phone; replacement bags for a vacuum

Similar products

Recommends products that are semantically or visually similar, without using any customer data.

Products meta information

Pink t-shirt and pink long sleeve t-shirt; sandals and slippers

Substitutes

Substitute products are alternate items that can be used in place of a desired item. They have the same features as the main product but may differ in price, availability, or quality.

Products meta information

Substitute wine with grape juice; substitute a low-priced handbag with a more expensive one

Same product upsell

Recommends the most expensive or cheapest products in the current cart or order, usually combined with a discount.

User cart and orders data

1 day

Free shipping upsell

Recommends products that could help reach the free shipping threshold when purchased.

User order and product price data

30 days

Trending

Recommends products that are currently trending in the store based on user views or orders within a few days.

Store clicked data

30 days

NextLLM

Real-time recommendations for the next best product series using a self-training multifaceted predictive model based on product tagging data and shopping behaviors from all AfterShipโ€™s stores.

Products meta information, store orders data, and user clicked data

30 days

Complete the look

Recommends different types of products that visually pair with a target product.

Products meta information

Shoes for a dress; rings for a bracelet

Recently viewed

Recommend products that the customer has viewed but not purchased. If applied on the product detail page, the currently viewed product will be excluded from the recommendations. Similarly, if used on the cart page, cart drawer, or smart cart, any products already in the cart will be excluded.

User clicked data

30 Days


Updated on: 07/03/2025