Product Recommendations

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What this section does

The Product recommendations section displays automatically-generated product suggestions powered by Shopify’s native recommendation engine. Features include:

• AI-powered recommendations: Shopify analyzes product relationships, purchase patterns, and customer behavior
• Dynamic content: Recommendations change based on the current product being viewed
• Customizable display: 2-10 products, adjustable heading, heading size
• Automatic updates: No manual product selection—recommendations improve over time
• Template-only section (usable on Product page template only)

Perfect for PDP cross-selling, “You may also like” sections, and increasing average order value through intelligent product discovery.

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Getting started

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Section settings

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Best practices

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Common use cases

Standard PDP cross-sell — Below product description, heading “You may also like”, 4-6 products for additional purchase suggestions Fashion/apparel completion — After “Add to Cart”, heading “Complete the look”, shows coordinating items (shoes with dress, belt with jeans) Electronics accessories — Bottom of PDP, heading “Customers also bought”, suggests cases, chargers, screen protectors for phones/laptops Home goods coordination — “Pairs well with”, suggests complementary decor items, matching furniture, coordinating colors Beauty product regimens — “Build your routine”, suggests complementary skincare steps, matching shades, full regimens Gift bundles — “Frequently bought together”, encourages multiple-item purchases for gifting or personal use

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How recommendations work

Shopify’s recommendation engine:

• Machine learning algorithm: Analyzes store-wide purchase patterns, view history, cart additions
• Product relationships: Identifies products frequently bought together or viewed in sequence
• Contextual relevance: Considers current product’s type, vendor, tags, collections, price range
• Real-time updates: Recommendations improve as more customer data accumulates

Recommendation sources:

1. Purchase history: Products bought together in past orders
2. Browsing behavior: Products viewed in same browsing sessions
3. Product similarity: Matching attributes (type, tags, vendor, collection)
4. Fallback logic: If insufficient data, shows products from same collection or vendor

Timeline for accuracy:

• New stores: Generic recommendations initially (same collection, random)
• Growing stores: Improves after 20-50 orders with those products
• Mature stores: Highly accurate after months of data collection

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Layout behavior

Desktop:

• Horizontal product grid (typically 4-5 products per row)
• Products displayed as cards: image, title, price, quick view/add button
• Section full-width or contained depending on theme defaults
• Heading centered or left-aligned above grid

Mobile:

• Horizontal scrollable carousel OR 2-column grid (theme-dependent)
• Swipe to see additional products
• Compact product cards optimized for touch
• Heading above grid/carousel

Empty state:

• If no recommendations available, section doesn’t display (hidden automatically)
• Common for brand-new products with no data
• Section remains in template but invisible to customers

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Maximizing recommendation quality

Product data optimization:

• Accurate product types: Set consistent product types (e.g., “Tops”, “Dresses”, not random text)
• Strategic tagging: Use tags for attributes (color, size, style, season)
• Logical collections: Group related products in collections (algorithm notices patterns)
• Vendor consistency: Standardize vendor names for brand-based recommendations

Store strategies:

• Bundle suggestions: Create bundles/kits to train algorithm on complementary items
• Related products: Manually link products via “Related Products” apps to influence recommendations
• Order history: Encourage repeat purchases—more data = better recommendations

Testing approaches:

• Test different heading text to see what drives clicks (“You may also like” vs “Complete the look”)
• Experiment with product count (4 vs 6 vs 8) and track engagement
• Monitor which recommendations get clicked most—inform manual curation elsewhere

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Related sections

• Recommended Products — Manual or API-powered recommendations (more control, custom products)
• Featured Products — Manually curated product showcases
• Recently Viewed — Browser-based recently viewed products section
• Complementary Products — Shopify Plus feature for curated complementary items

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Technical notes

Shopify Recommendations API: This section uses Shopify’s recommendations/products API endpoint. Completely server-side, no merchant configuration needed beyond section settings. Template requirement: Only functions on Product template (main-product.liquid or equivalent). Other templates lack product context for recommendations. Recommendation limits: Shopify API can return 0-10 products per request. Empty response = section hidden automatically. Performance: API call is server-side during page render. No client-side JavaScript delays. Recommendations rendered同步 with page load. Intent types: Shopify’s API supports related (default, most common) and complementary intent types. This section typically uses related—products similar or frequently bought together. Fallback behavior: If recommendations unavailable (new product, insufficient data), API returns empty array. Theme handles gracefully by hiding section. No configuration required: Unlike apps, no backend setup, no manual product linking. Fully automatic based on store data. Shopify Plus note: Shopify Plus stores have access to additional recommendation features and customization via App extensions and API customization.

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Customization beyond settings

Liquid customization (for developers):

• Adjust product card design (image ratio, show/hide elements)
• Change grid layout (products per row, gaps)
• Customize empty state messaging
• Add custom intent types (related vs complementary)

CSS customization:

• Style product cards, hover states, buttons
• Adjust heading typography, colors, spacing
• Modify grid gaps, responsive breakpoints

JavaScript enhancements:

• Add quick view modals for recommended products
• Track recommendation click analytics
• Implement custom product card interactions

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Troubleshooting

No recommendations showing:

• New product: Requires purchase/view history to generate recommendations
• Insufficient data: Store needs more orders for algorithm to identify patterns
• Product mismatch: No similar products in catalog for algorithm to match
• Template placement: Confirm section is on Product template, not other templates

Poor recommendation quality:

• Improve product data: Add/fix product types, tags, collections
• Increase catalog: Larger catalogs provide more recommendation opportunities
• Wait for data: New stores need time to accumulate behavioral data
• Check related apps: Some apps interfere with Shopify’s recommendations

Section displaying incorrectly:

• Theme compatibility: Ensure theme supports native product recommendations
• Customization conflicts: Custom code may override section styling
• Product count: Try adjusting product count setting (some themes handle counts differently)