Your Store Isn't a Brochure. It's an Optimization Engine.
A letter to commerce experience teams: Generic best practices won't grow your store. You need three disciplines working together—full-stack testing, shopper personalization, and strategic merchandising.
Discover how leading brands lift AOV by 20%+.
Watch how commerce teams use testing, personalization, and merchandising to grow AOV.
Chapter 1
The Commerce Reality
Most stores rely on generic best practices—the same checkout flow, the same product pages, the same recommendations as everyone else. But your products, your customers, your markets are unique. What works for a fashion brand in France won't work for a supplement brand in the US.
Full-Stack Testing
Test pricing, checkouts, assortments, and page layouts—not just button colors. Optimize for YOUR specific products and markets.
Shopper Personalization
No two shoppers see the same store. Personalize based on purchase history, browsing behavior, and real-time intent signals.
Strategic Merchandising
The right recommendations in the right context—homepage, category, PDP, checkout. Each page type needs a different strategy.
Chapter 2
Full-Stack Testing Beyond Buttons
Real optimization isn't about testing button colors. It's about testing your entire commerce stack—checkout flows, pricing strategies, product assortments, page layouts. Test deeply across product pages, category pages, detail pages, and checkout flows.
Test checkout flows deeply
A/B test entire checkout experiences, payment options, shipping displays, and trust signals—not just surface elements.
Optimize for your markets
What converts in Germany differs from the UK. Test pricing, messaging, and layouts by country and customer segment.
Measure real revenue impact
See the exact revenue lift from each test. Know which changes actually moved conversion and AOV.
Chapter 3
No Two Shoppers See the Same Store
Take your testing winners and personalize your website for the segments that matter. Personalize based on previous purchases, current browsing patterns, and real-time intent. Every shopper gets a store optimized for them.
Purchase-based personalization
Show returning customers products that complement their purchase history. First-time buyers see bestsellers.
Browsing behavior targeting
Adapt in real-time to what shoppers are looking at. Category interest, price sensitivity, brand affinity.
Segment-level targeting
Define the segments your store should personalize for—VIP customers, deal seekers, category enthusiasts.
"GrowthOS unified our online shopping behavior and helped us drive smarter upsells with far less manual effort."
— Titas Kumpys, CEO, Trolių namas
Chapter 4
Merchandising From Homepage to Checkout
Different pages need different recommendation strategies. Homepage shows what's popular. Category pages show affinity. Product pages show "also bought." Checkout shows cross-sell and upsell opportunities. One brain, many contexts.
Context-aware algorithms
"People who bought this" on PDPs. "Complete the look" on category. "Add before you go" at checkout.
Cross-sell and upsell at checkout
Surface high-margin add-ons, bundles, and upgrades at the moment of highest purchase intent.
Measure AOV by placement
See which recommendation placements drive the most revenue. Optimize strategy per location.
Unlock Commerce Growth Plays
Explore proven playbooks for testing, personalization, and merchandising. Filter by goal—conversion optimization, AOV growth, cross-sell strategies—to discover tactics that work for your store.
Frequently Asked Questions
Everything you need to know about personalization and AOV optimization
Intempt uses real-time browsing behavior, purchase history, and product affinity signals to serve relevant recommendations across your site, emails, and SMS—not just static bestseller lists.
Yes. The same recommendation strategies power your website, email blocks, and SMS links, so customers see consistent, personalized suggestions everywhere.
Intempt automatically swaps out-of-stock items for available alternatives based on your configured fallback rules—no manual intervention required.
Shopify's built-in recommendations are limited to basic 'also bought' logic. Intempt lets you configure cross-sell, lookalike, margin-focused, and bundle strategies with full control and testing.
Most teams see measurable AOV lift within 2-4 weeks of deploying personalized recommendations and cross-sell strategies across key placements.
Ready to grow AOV with smarter recommendations?
Let Blu orchestrate your product discovery across every touchpoint.