How can I use 'people also bought' recommendations effectively?

Question

I'm struggling to implement effective cross-selling strategies in my e-commerce store. While I understand the concept of 'people also bought' recommendations, I'm unsure how to execute them in a way that genuinely increases average order value and provides real value to customers. I want to create recommendations that feel authentic, helpful, and not just like a random sales tactic. What are the best practices for designing recommendation algorithms that actually convert and enhance the shopping experience?

Muhammed Tüfekyapan · Accepted Answer

Using 'People Also Bought' Recommendations Effectively
"People also bought" is one of e-commerce's most powerful AOV levers - Amazon attributes up to 35% of revenue to recommendation algorithms. But the strategy only works when recommendations feel genuinely useful rather than random upsells. The key is relevance: the recommended item must logically complement what the customer already wants.

Recommendation Placement Strategy

Location
      Recommendation Type
      Goal

Product page (below fold)
      Frequently bought together
      Pre-purchase bundle consideration

Cart page / drawer
      Complementary add-ons
      Last-moment AOV increase

Post-purchase page
      Related products, accessories
      Second purchase without abandonment risk

Email (order confirmation)
      What goes with your purchase
      Warm audience cross-sell

What Makes Recommendations Convert

Logical pairing - Camera bag with camera, not another camera
  Price compatibility - Add-ons should be 20-40% of the main item's price
  Social framing - "87% of customers who buy X also get Y" is more persuasive than generic "you might like"
  One-click add - Friction kills impulse adds; let customers add without leaving the page
  Bundle discount option - "Add both for $X, save $Y" significantly boosts uptake

Recommendation Mistakes to Avoid

Recommending competitors or substitutes - visitors may switch instead of add
  Showing too many options (more than 4-5) - paradox of choice reduces conversion
  Recommending out-of-stock items - kills trust and wastes the moment
  Generic "bestsellers" with no relevance to the viewed product

AI-Powered Cart Recommendations
  Growth Suite's Advanced Cart Drawer includes AI-powered product suggestions that surface genuinely complementary items based on cart contents and purchase history. The Frequently Bought Together widget automatically identifies high-affinity product pairs from your store's actual order data - eliminating the guesswork of manual curation while maximizing relevance.

How can I use 'people also bought' recommendations effectively?

TL;DR - Quick Answer

Complete Expert Analysis

Using 'People Also Bought' Recommendations Effectively

Recommendation Placement Strategy

What Makes Recommendations Convert

Recommendation Mistakes to Avoid

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Muhammed Tüfekyapan

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Use Cases

Location	Recommendation Type	Goal
Product page (below fold)	Frequently bought together	Pre-purchase bundle consideration
Cart page / drawer	Complementary add-ons	Last-moment AOV increase
Post-purchase page	Related products, accessories	Second purchase without abandonment risk
Email (order confirmation)	What goes with your purchase	Warm audience cross-sell