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GrowthDecember 20, 202410 min read

How to Increase AOV by 40% with Product Recommendations

AI-powered product recommendations are the fastest way to increase average order value. Here's exactly how top brands are doing it—with specific strategies you can implement today.

OA
Octane AI Team
Growth & Strategy
📈

Every ecommerce operator knows the math: it costs nearly the same to acquire a customer who spends $50 as one who spends $150. That's why increasing average order value (AOV) is one of the highest-leverage activities in ecommerce. And personalized product recommendations are the most effective way to do it.

The AOV Opportunity
$75 → $105
Average AOV increase with personalized recommendations
40%
Avg. AOV lift
35%
Of revenue from recs
10x
Higher engagement

Why Generic Recommendations Fail

Most ecommerce stores use the same recommendation widgets: "Customers also bought," "You might also like," "Bestsellers." These are better than nothing, but they're fundamentally limited because they're based on aggregate behavior, not individual preferences.

A customer with oily, acne-prone skin sees the same "popular products" as someone with dry, mature skin. That's not personalization—it's just popularity.

The Generic Rec Problem: "Customers who bought this also bought..." recommendations have an average click-through rate of just 2-3%. Personalized recommendations based on zero-party data see 15-25% CTR.

The Personalized Recommendation Playbook

Here are the specific strategies top brands use to increase AOV with personalized recommendations:

1Quiz-Based Bundle Recommendations

Use quiz answers to recommend complete routines or bundles instead of single products. A customer who says they want to "build a full skincare routine" is primed to buy 4-5 products, not just one.

Example Result:
Your Complete Morning Routine
Gentle Cleanser$28
Vitamin C Serum$45
Daily Moisturizer$38
SPF 50 Sunscreen$32
Bundle Total
$143$119
✓ Average 2.4x higher AOV vs. single product pages
2Smart Cross-Sells Based on Quiz Data

Use quiz responses to power cross-sells throughout the customer journey. If someone indicated they have "sensitive skin" in the quiz, show them gentle, fragrance-free options in cart cross-sells—not just bestsellers.

Cart Cross-Sell (Personalized)
"Based on your sensitive skin, add our Calming Toner for complete protection"
Calming Rose Toner
For sensitive skin
3Personalized Email Product Blocks

Sync quiz data to Klaviyo and use it to personalize product recommendations in every email. Instead of showing the same "Shop Now" products to everyone, show products matched to their quiz responses.

❌ Generic Email
"Check out our bestsellers!"
3.2% CTR average
✓ Personalized Email
"Products matched to your oily, acne-prone skin"
18.7% CTR average
4Tiered Result Pages

Show customers Good/Better/Best options at different price points. This anchors value and often leads customers to choose the middle or premium tier.

Starter
$49
3 products
Popular
Complete
$89
5 products
Premium
$149
7 products
✓ 62% of customers choose middle or premium tier
5Subscription Upsells

Use quiz data to identify subscription-ready customers. Someone who indicated they want a "consistent routine" or has "replenishment needs" is a great candidate for a subscribe-and-save offer.

Subscribe & Save 20%Best Value
Get your personalized routine delivered every 30, 60, or 90 days

Implementation Checklist

Ready to implement these strategies? Here's your action plan:

Your AOV Optimization Checklist

  • Build a product quiz that captures preferences and goals
  • Create bundle recommendations for quiz results pages
  • Set up personalized cross-sells in cart based on quiz data
  • Sync quiz data to Klaviyo for personalized email product blocks
  • Add Good/Better/Best tiers to your results page
  • Test subscription upsells for repeat-purchase products

Measuring Success

Track these metrics to measure the impact of your personalized recommendations:

  • AOV: Compare quiz purchasers vs. non-quiz purchasers
  • Items per order: Are customers buying more products?
  • Cross-sell conversion: % who add recommended products
  • Bundle adoption: % choosing bundles vs. single products
  • Email revenue per recipient: Personalized vs. generic emails
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