Personalization & AI

Product Recommendations

Algorithmically suggested products based on browsing and purchase history.

1 min readLast updated Apr 2026

Algorithmically suggested products based on browsing and purchase history.

Why It Matters

Product recommendations can drive 10-30% of total ecommerce revenue and significantly increase AOV through cross-sells.

Practical Example

Scenario

A home goods store adds 'Complete the Look' recommendations on product pages.

Calculation

1,000 orders/month × $85 AOV = $85,000. With recommendations adding $15 per order: $100,000

Result

18% increase in AOV, adding $15,000/month in revenue from recommendation-influenced purchases

Pro Tips

  • 1Test recommendation placement—below add-to-cart often outperforms sidebar positioning
  • 2Use 'bought together' for cross-sells and 'similar items' for alternatives strategically
  • 3Exclude items customers already own using purchase history data

Common Mistakes to Avoid

Showing the same recommendations everywhere instead of context-appropriate suggestions
Recommending lower-priced items when customer is viewing premium products
Not filtering out-of-stock items from recommendation widgets

Frequently Asked Questions

Related Terms

Personalization

Tailoring website content and product recommendations to individual users.