Commerce AI UX patterns
Commerce patterns for discovery, recommendations, visual search, and checkout flows augmented by AI.
Essential
Find by meaning or image, cart across merchants, compare, and complete the buy.
More in Commerce
Commerce
Smart Recommendations
Context-aware product suggestions
Commerce
Smart Comparison
Build dynamic product or option comparison tables
Commerce
Natural Language Filter
Natural language to editable filter chips
Commerce
Smart Form Fill
Parse unstructured text into form fields
Commerce
Smart Bundles
Context-aware complementary product offers
Commerce
Review Summary
Pros, cons, and themes from many reviews
Commerce
Price Drop Alerts
Notify users of price changes
Commerce
Dynamic Pricing
AI-powered real-time price optimization
Commerce
Inventory Prediction
Predict stock needs based on trends
Commerce
Return Prediction
Predict likelihood of returns
Commerce
Personalized Checkout
Custom checkout flow per user
Commerce
AI-Powered Customer Support
Proactive support suggestions
Commerce
Fraud Alert
Verify suspicious acts
Frequently asked questions
When should I use commerce AI patterns?
When search, recommendations, or merchandising are core journeys and users need natural language or multimodal discovery, not only a generic chat sidebar bolted on.
What is the difference between semantic search and NL filters?
Semantic search retrieves by meaning across catalog content. NL filters translate phrases into structured facets users can still edit, combine them so power users can correct the query.
How should visual search handle low confidence?
Show similar matches with clear “best guess” labeling and easy pivot to text search. Visual search fails on ambiguous photos; recovery paths matter more than perfect first hit.
Where do smart bundles and recommendations fit?
Use on PDP, cart, and post-add-to-cart surfaces when context is rich. Explain why items are grouped so users don’t feel manipulated by opaque AI merchandising.
Do commerce patterns cover post-purchase AI?
Yes. Review summaries, support handoff, and return flows appear in the catalog. Pair transactional patterns with trust signals when money or personal data is involved.
Can I benchmark against real storefronts?
Each pattern lists example retailers and marketplaces; case studies in the gallery complement patterns with full-page screenshots.