How many types of product recommendations do you need? (Shein vs. Amazon approach)
Product recommendations aka “You recently viewed”, “Related items”, and “What others bought” have become common occurrences nowadays. There are first popularized by Amazon as a tool for upselling and cross-selling products (sales conversion/optimization). Now you can find product recommendations on most major e-commerce stores.
The idea of product recommendations is similar to traditional physical stores where products are organized in departments and in extreme cases such as Ikea where the store layout is designed intentionally to keep you shopping longer.
The many types of product Recommendations
Some of the common product recommendations include:
Frequently Bought Together
The basic psychology behind this type of recommendation is to upsell additional complementary products the shopper might need. (For example, show bicycle lock, spare tube, and helmet when someone is looking at purchasing a bike)
Tip: look for a recommendation app that allows you to offer discount or additional incentive when purchasing bundled products
What Others Liked/Bought/Viewed
This type of product recommendation looks at shoppers browsing behavior and presents items that may be interesting to users that are deemed “similar”. It is one of the first popularized machine-learning product recommendation algorithms from Amazon.
Tip: This is good for recommending items across different product categories since shoppers browsing session can vary dramatically. The products recommended also refreshes to reflect the seasonality (e.g. Christmas items during the holidays)
Similar Products
This type of product recommendation will present items that are similar (e.g. Show bigger or smaller TVs when a shopper is looking at a TV). The primary benefit of this is to minimize abandonment if a shopper does not find what they are looking for immediately.
This type of recommendation can be machine-learning based or manual such as tagging/taxonomy-based
Other types…….
There are also other types of product recommendations such as “recently viewed items”, “popular items”, “products on sale”, etc.
One Recommendation (rules them all?)
Instead of presenting many different product recommendations on the screen, some stores only present one set of product recommendations.
A primary example of this is Shein.com, one of the most popular e-commerce stores at the moment. Shein presents one set of product recommendations that continues to load, offering users a full browsing experience.
The recommendations are a mix of similar products and what the user has recently viewed.
The bottom line
Product recommendations have proved they are here to stay. However, there is no definite answer to your approach in presenting multiple recommendations (Amazon approach) or a single recommendation type (Shein approach).
To know what works for you still requires extensive A/B testing and data analytics.
Siggy is a Machine-learning/AI-based product recommender for Shopify. If you run a Shopify Store, you can Try Siggy Free
