Frequently Bought Together & Product Recommendations on Shopify
Learn how to use product recommendations on Shopify. Covers Frequently Bought Together, trending products, placement strategy, AI vs manual curation, and performance tracking.
Muhammed Tüfekyapan
Key Takeaways
- 1 Product recommendations are the most passive upsell strategy. Set them up once and they run on every page, every visit, automatically. No pop-ups. No manual triggers.
- 2 There are four main recommendation types: Frequently Bought Together, Trending Products, Related Products, and Recently Viewed. Each uses a different data source and serves a different purpose.
- 3 FBT needs at least 50-100 orders to find meaningful patterns. New stores should start with manual curation or trending products until they have enough order history.
- 4 Placement matters more than the algorithm. FBT belongs on product pages. Trending products belong on the homepage and collection pages. Complementary add-ons belong in the cart.
- 5 The hybrid approach works best for most stores. Let the algorithm handle 80% of your catalog. Manually curate the 20% that matters most - top sellers, seasonal items, and high-margin products.
- 6 Measurement is the biggest gap. If you do not track click-through rates and revenue per recommendation widget, you cannot improve. Set up analytics before anything else.
Some upsell strategies need constant work. You build pop-ups. You write offers. You manage triggers. Product recommendations Shopify is not like that. You set them up once. Then they run on every product page, every collection page, and every homepage visit. Automatically. No manual work. No daily management. Just passive revenue on every visit.
Think about it. You have product pages. Collection pages. A homepage. A cart. Each one is a chance to show a relevant product suggestion. Most Shopify stores use zero of these touchpoints. Or they use Shopify's basic defaults and never think about it again. That is money left on the table every single day.
This guide covers everything about frequently bought together Shopify and other recommendation types. What they are. How they work. Where to place them. How to measure them. And how to build a complete product recommendations Shopify strategy that runs on autopilot.
There are four main types. Frequently Bought Together. Trending Products. Related Products. Recently Viewed. Each one serves a different purpose. Each one converts differently. The best stores use all four. Let's break them down.
Tip: Product recommendations are the only upsell strategy that works passively on every page. No pop-ups. No interruptions. No manual triggers. Set them up correctly and they generate revenue on every visit automatically.
What Are Product Recommendations and How Do They Work?
Product recommendations Shopify are automated suggestions that show relevant products to your shoppers. They use data to decide what to show. Not your opinion. Not your gut feeling. Real data from your store.
There are four main types. Each uses a different data source. Each works best in a different location.
Frequently Bought Together (FBT)
FBT looks at your order history. It finds products that customers buy in the same order again and again. If 40 out of 200 customers who bought running shoes also bought performance socks, FBT shows socks on the running shoes page. This is the "Customers who bought this also bought" format that Amazon made famous.
Trending Products
Trending products show what is popular right now. Not last month. Not last year. Right now. The data source is real-time store activity. Views, add-to-carts, and purchases from the last few hours or days. It changes constantly based on what shoppers are doing today.
Related Products
Shopify related products suggest items from the same collection, with similar tags, or in the same category. The data source is your product metadata. How you tag and organize your products determines what gets suggested. It is the simplest type but also the least personalized.
Recently Viewed
Recently Viewed shows products the current visitor already looked at. The data source is their browsing session. This is powerful for returning visitors. They showed interest before. Bring them back to those products immediately.
| Recommendation Type | Data Source | Best Placement | Purpose |
|---|---|---|---|
| Frequently Bought Together | Historical order data | Product page | Complementary purchases |
| Trending Products | Real-time store activity | Homepage, collection page | Social proof, discovery |
| Related Products | Product tags, collections | Product page, collection page | Category exploration |
| Recently Viewed | Individual browsing session | Homepage, all pages | Return visit conversion |
Key Insight: Each recommendation type uses a different data source and serves a different purpose. FBT uses purchase history. Trending uses real-time activity. Related uses product metadata. Recently Viewed uses browsing history. The best strategy combines all four.
How to Add Product Recommendations to Your Shopify Store
You have two options for adding product recommendations Shopify. Use Shopify's built-in tools. Or use a third-party app. The choice depends on what you need.
Shopify's Built-in Options
Shopify offers a basic recommendation feature through its Search & Discovery app. It provides related products and some complementary product suggestions. It works for basic setups. But it has limits. No dedicated FBT algorithm. No trending products. Limited customization. Basic analytics at best.
What Third-Party Apps Add
A dedicated recommendation app gives you more. Multiple recommendation types. Smarter algorithms that learn from your data. Native theme integration that looks like part of your store. Placement flexibility across all pages. And real performance tracking so you know what works.
The Data Requirement Most Merchants Miss
Here is what nobody tells you. Different recommendation types need different amounts of data to work well.
- FBT needs order history. You need at least 50-100 orders for the algorithm to find meaningful patterns. New stores should start with manual product curation until they have enough data.
- Trending Products needs traffic. It works best for stores with 100 or more daily visitors. Without regular traffic, there is not enough activity to identify trends.
- Related Products needs proper tagging. The quality of your suggestions depends on how well you organize your products. Bad tagging means bad suggestions.
Warning: FBT needs order history to work. If your store has fewer than 50 orders, start with manual product curation or trending products. Switch to algorithmic FBT once you have enough purchase data for the algorithm to find patterns.
What to Look For in a Recommendation App
When you evaluate shopify product suggestions apps, look for these features:
- Multiple recommendation types: Not just one. You want FBT, trending, and related products.
- Native theme integration: The widget should look like part of your store. Not an ugly iframe.
- One-click Add to Cart: Customers should add products from the recommendation widget without leaving the page.
- Performance analytics: Views, clicks, add-to-cart rate, and revenue attributed to each widget.
- Mobile-optimized display: More than 60% of Shopify traffic is mobile. The widget must work perfectly on phones.
Frequently Bought Together - The Highest-Converting Recommendation Type
Frequently bought together Shopify is the recommendation format every shopper recognizes. Amazon made it famous. "Customers who bought this also bought..." It is now the standard for product page upsell Shopify strategies. And it converts higher than any other recommendation type.
How the FBT Algorithm Works
The algorithm is straightforward. It scans all your historical orders. It finds products that appear together in the same order above a certain threshold. When a customer views Product A, the system shows the products most commonly purchased alongside Product A.
As more orders come in, the pairings update automatically. The algorithm gets smarter with every sale. A product that was rarely paired six months ago might become a top pairing today as buying patterns shift.
Why FBT Converts Higher Than Other Types
Three reasons. First, social proof. "Other customers bought these together" is a powerful signal. It says: this combination works. Second, convenience. The products are pre-selected. One click adds them all. Third, relevance. The pairings come from actual purchase data. Not guesswork.
FBT click-through rates typically range from 3-5%. That is higher than related products (1-3%) and you may also like Shopify widgets (2-3%). The data-driven nature of FBT is what makes the difference.
Manual vs Algorithmic FBT
You can set up FBT two ways. Algorithmic means the system discovers pairings from your data. Best for stores with 100 or more orders and diverse product catalogs. Manual means you hand-pick every pairing. Best for new stores, niche products, or curated brands.
Most stores do best with a hybrid approach. Let the algorithm run. Then review the top pairings and override the ones you know better. The algorithm handles your catalog's long tail. You focus on your top 10-20 products.
The "Complete the Look" Variant
Same FBT logic. Different presentation. Instead of "Frequently Bought Together," you show "Complete the look Shopify" or "Goes Great With." This works especially well for fashion, beauty, and home decor. The language feels more curated and lifestyle-oriented.
Key Insight: Frequently bought together Shopify recommendations convert higher than other types because they are based on what real customers actually buy together. This is not guesswork. It is data from your own store's order history. The algorithm gets smarter with every order.
Trending Products - Showcasing What Is Selling Now
Trending products answer the question every shopper has: "What are other people buying right now?" That question drives social proof. And social proof drives purchases.
Trending vs Best-Selling
These are not the same thing. Best-sellers are a static list based on total historical sales. They change slowly. A product that sold well last month might not be moving now. But it still sits on your best-seller list.
Trending is different. It is a dynamic list based on real-time activity. Views, add-to-carts, and purchases from the last few hours or days. It changes frequently. It reflects what is actually hot right now. Not what was hot last quarter.
Example: Winter boots might be your best-seller in total sales. But in spring, sandals are trending. A best-seller list shows boots. A trending list shows sandals. Which one helps your customer more in April?
How Trending Creates Social Proof
The bandwagon effect is real. People want what other people want. A shopify popular products section that says "Trending Now" creates genuine social proof. It is not manufactured urgency. It is real data about what real shoppers are doing right now.
Trending widgets also help with discovery. Customers find products they did not search for. They see what is popular and explore from there. This is especially powerful on the homepage where visitors are in browsing mode.
Placement for Trending Products
Homepage is the highest-impact placement. It is the first page many visitors see. A dynamic trending section signals that your store is active and popular. Collection pages work well too. "Popular in This Category" highlights what other shoppers prefer within a specific category.
Seasonal Rotation
Trends change with seasons, promotions, and holidays. Manual curation cannot keep up. By the time you update a best-seller list, the trend has already shifted. Automated trending products rotate in real time. No merchant work needed. Your store always shows what is relevant today.
Tip: Trending products are the simplest recommendation type to start with. They need no order history and no product pairing. Just traffic. If your store gets regular visitors, trending products work immediately.
Where to Place Recommendations for Maximum Conversion
The best algorithm in the world does not matter if nobody sees the widget. Product recommendation placement is the difference between a widget that generates revenue and one that generates nothing. Where you put it matters more than how smart it is.
Product Page - Below the Fold
This is the classic FBT position. Customers who scroll past the main product details are engaged. They are actively considering the purchase. Show them what goes with it. Frequently bought together Shopify widgets work best here. Click-through rates: 3-5%.
Product Page - Sidebar
Shopify related products or "You May Also Like" work in the sidebar on desktop. Customers can browse alternatives without leaving the page. On mobile, sidebars stack below the main content. Less effective on phones.
Collection Page
Collection pages are browsing pages. Customers are exploring. They are not committed to anything yet. "Popular in This Category" or shopify popular products sections help undecided shoppers find proven products. Position them at the top of the collection or between product rows.
Homepage
The homepage is the first touchpoint for many visitors. Trending products show store vitality and create immediate engagement. Recently Viewed sections are powerful for returning visitors. They showed interest before. Bring them back to those products right away.
Cart Page and Cart Drawer
The cart is your last chance before checkout. "Customers Also Bought" or "Complete Your Order" sections work here. Keep the recommended products small and affordable. A $5 add-on in the cart is an easy yes. A $50 product makes customers rethink their entire purchase.
| Placement | Best Recommendation Type | Goal | Typical CTR |
|---|---|---|---|
| Product page (below fold) | Frequently Bought Together | Complementary purchase | 3-5% |
| Product page (sidebar) | Related Products | Category exploration | 1-3% |
| Collection page | Trending Products | Social proof, discovery | 2-4% |
| Homepage | Trending + Recently Viewed | Quick product access | 2-3% |
| Cart page/drawer | Complementary add-ons | Last-chance upsell | 1-3% |
Key Insight: Each page on your store serves a different recommendation purpose. Product pages are for complementary purchases (FBT). Collection pages are for discovery (trending). The homepage is for quick access (trending + recently viewed). The cart is for last-chance add-ons. Use the right type in the right place.
Mobile Placement Rules
More than 60% of Shopify traffic is mobile. Your recommendation widgets must work perfectly on phone screens. Keep these rules in mind:
- Show 2-3 products per row. Not 4-5 like desktop. Use horizontal scroll carousels.
- Keep Add to Cart buttons tappable. Thumb zone matters. Buttons must be large enough to tap easily.
- Stay in the scroll path. If a customer has to tap to expand a section, most will not. Recommendations must be visible in the natural scroll flow.
- Load fast. Slow-loading widgets hurt the entire page experience. Speed matters especially on mobile.
AI-Powered vs Manual Product Recommendations
"Should I pick the products myself or let an algorithm decide?" This is the most common question merchants ask about shopify ai product recommendations. The answer is: it depends on your store.
Manual Curation
You select specific product pairings. "When viewing the blue dress, show the matching belt and earrings." You have complete control. It works with zero data. Perfect for curated brands and luxury stores. The downside: it does not scale. 100 products means hundreds of pairings to manage. And you are limited by your own assumptions about what customers want.
AI-Powered Recommendations
Shopify ai product recommendations analyze your data to find patterns humans miss at scale. The algorithm looks at order history, browsing behavior, and product attributes. It identifies statistical correlations. "Customers who bought X have an 18% probability of also buying Z." It improves over time. More data means better suggestions.
The catch: AI needs data to work. This is the cold start problem. A new store with 20 orders cannot generate meaningful algorithmic pairings. You need at least 50-100 orders for basic patterns. 200 or more orders for reliable automated suggestions.
When Each Approach Wins
Manual wins when: your catalog is small (under 50 products), your store is new (under 50 orders), your brand is highly curated, or you know your product relationships better than any algorithm could.
AI wins when: your catalog is large (100+ products), you have high order volume (200+ per month), your product range is diverse, or you cannot maintain manual pairings at scale.
The Hybrid Approach
Most stores do best with a hybrid. Let the algorithm handle 80% of your catalog. Manually curate the 20% that matters most. Your top-selling products, seasonal items, and high-margin products get manual attention. Everything else runs on autopilot.
Tip: You do not have to choose between AI and manual. The hybrid approach lets the algorithm handle the heavy lifting while you override specific pairings and pin seasonal products. Data-driven efficiency with human judgment. Best of both worlds.
Common Product Recommendation Mistakes
Product recommendations Shopify are simple to set up. That simplicity makes it easy to get them wrong and never look back. Here are the six mistakes that cost stores the most revenue.
Mistake 1: Using Only One Recommendation Type
Many stores add FBT to product pages and call it done. But a product page needs FBT. The homepage needs trending. The cart needs add-ons. Different types serve different purposes. Using just one is like opening one register in a 10-register store.
Mistake 2: Bad Placement
Recommendations buried in a tab or collapsed section get zero visibility. Nobody clicks a tab to see product suggestions. The widget must be in the natural scroll path. Visible without any extra interaction.
Mistake 3: Ignoring Mobile
More than 60% of your traffic is on phones. If your upsell recommendations Shopify widget looks broken on mobile, you are missing the majority of your visitors. Test on real devices. Not just your desktop browser.
Mistake 4: No Measurement
If you do not track click-through rates and add-to-cart rates per recommendation widget, you have no idea what works. You cannot improve what you do not measure. At minimum, track: impressions, clicks, add-to-cart, and attributed revenue.
Mistake 5: Set It and Forget It
Product catalogs change. Best-selling items shift. Manual pairings go stale. The recommendation setup you created six months ago might not be right today. Review your recommendation performance at least quarterly.
Mistake 6: Too Many Products in the Widget
Showing 8-10 products in a recommendation carousel creates decision paralysis. The shopper sees too many options and picks none. Three to four products is the sweet spot. Enough choices to be helpful. Few enough to be decisive.
Warning: The biggest mistake is not measuring. If you do not track click-through rates and revenue per recommendation widget, you are flying blind. You cannot optimize what you do not measure. Set up analytics before anything else.
How Growth Suite Powers Product Recommendations
Most recommendation apps offer one type. Growth Suite provides a complete recommendation system with two engines and detailed analytics. Here is what it includes.
Trending Products
Growth Suite's Trending Products feature identifies items with the highest current engagement across your store. It looks at real-time data: views, add-to-carts, and purchases. Products with the most activity surface automatically. No manual curation needed. The list updates in real time as customer behavior shifts.
You can place shopify popular products widgets on your homepage, collection pages, or product pages. Each placement serves a different purpose. Homepage drives discovery. Collection pages highlight category favorites. Product pages show alternatives.
Frequently Bought Together
Growth Suite's FBT analyzes your historical order data to find product combinations that customers actually buy together. It displays these on product detail pages as "Frequently bought together Shopify" or "Complete the look Shopify" sections.
You get both algorithmic and manual modes. Let the algorithm discover pairings from your data. Or hand-pick specific combinations for your top products. The hybrid approach works best for most stores.
Native Theme Integration
Both recommendation engines integrate natively with any Shopify theme. Desktop and mobile. The widgets match your store's design automatically. No ugly iframes. No code conflicts. Full customization is available through the Shopify theme customizer. No coding required.
One-Click Add to Cart
Customers add recommended products without leaving the current page. One click. The product goes straight to cart. No page redirects. No interruptions. Frictionless shopify upsell on product page experience.
Performance Tracking
Track views, clicks, add-to-cart rates, and attributed revenue for every recommendation widget. See which product recommendations Shopify placements drive the most revenue. Compare FBT performance against trending product performance. Use the data to optimize your strategy over time.
Key Insight: Growth Suite combines Trending Products and Frequently Bought Together in one platform. Both integrate natively with your Shopify theme. Both offer one-click add-to-cart. And both provide detailed performance analytics so you know exactly what drives revenue.
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Muhammed Tüfekyapan
Founder of Growth Suite
Muhammed Tüfekyapan is a growth marketing expert and the founder of Growth Suite, an AI-powered Shopify app trusted by over 300 stores across 40+ countries. With a career in data-driven e-commerce optimization that began in 2012, he has established himself as a leading authority in the field.
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