The Psychology Behind “You May Also Like”

Have you ever thought about the titles that usually appear above your product recommendations?

These are called “sorting cues” and they guide visitors towards highlight content. However, these few words can have a massive impact on the success metrics delivered by personalised product recommendations, including derived revenue and clickthrough rates.

Hidden Meanings

Whilst you might think each phrase accurately describes the “logic” behind the recommendations, usually titles are interchangable and bear no relation to how the products are decided.

However, to your users each one is subtly different.

Social Proof

Sorting cues such as “Popular Today”, “Best Sellers” and “People Who Bought This Also Bought” might be used to promote social proof. Social proof is often used where users may be uncertain or need to reinforce an impending decision.

“Popular Today”, “Best Sellers” and other similar sorting cues are often used on homepages, but any social proof derived from this is really only useful to returning visitors who are seeing the product they are returning to buy there.

Using “People Who Bought This Also Bought” on product pages can detract the visitor from their original goal by conveying “cross-sell” opportunities and presenting more choice – similar to what we found looking at product recommendations when scrollers were used.

Rather than push users away from the product they are looking for, we advocate using “up-sell” logic to suggest similar but more expensive product. Here, the cue “People Who Looked At This Also Looked At”, or “People Who Looked At This [Eventually] Bought” is more appropriate as it suggests both the right “logic” and uses social proof to push visitors towards more expensive products, increasing average order value.


This is a favourite of ours – using authority and expert-ship to drive users towards recommended products. However, they can sometimes present obstacles to visitors who are yet to declare an intention in a product category or preferences towards colours, styles, brands, etc.

“Editor’s Picks” are very handy for fashion sites that create or curate content, driving great results for sites which have a loyal following who have ‘bought in’ to the brand and their story. This sorting cue can be used anywhere on a site, but are especially great for directing new or returning visitors towards products they wouldn’t usually be interested in – usually on the homepage. “We Like” is another interchangable sorting cue that conveys similar meaning but may be more suited for non-fashion sites such as electronics or gadgets.

“Complete The Outfit”, “Get The Look” and the like are useful for fashion retailers for increasing average order values, however are typically seen on product pages to promote cross-sell products. We would advise using similar sorting cues on a cart page, suggesting cross-sell products usually with a maximum price, to act as “no-brainers”.


A little used on-site psychological strategy, scarcity can be used well in email marketing. Using sorting cues such as “Last Chance” or “Get Them Before They’re Gone”  work by directing users to believe products are more important because of a lack of availability, and also leads back to the social proof tactic described above.


“Recommended For You” is a great way to direct users towards content they know is personalised and just for them. Best used on “My Account” pages, these instill importance and curation – an interesting approach would be to use a Pinterest-style layout with recommended products and blog posts, pushing the boundaries of blended content further.

Test, Test and Test.

It’s 2012 – every retailer should be testing every part of their ecommerce site looking to increase conversions and revenue – testing sorting cues should be no different.

Multivariate testing will allow many combinations of sorting cues in different areas all over the site to find the combination which presents the best results. By split testing the “logic” behind the recommendations, retailers can  optimise their personalisation strategies to continuously improve results.