How to Set Up Frequently Bought Together on Shopify
Learn how to set up Frequently Bought Together on Shopify with algorithmic and manual pairings. Covers how FBT algorithms work, the cold start problem, widget setup, and performance measurement.
Muhammed Tüfekyapan
Key Takeaways
- 1 Frequently bought together works because the suggestions come from real orders, not guesses. Social proof plus one-click convenience is what makes shoppers add the extras.
- 2 FBT algorithms need real order data to work. Stores with fewer than 50 orders should start with manual picks, and at 200+ orders the algorithm produces reliable pairings across the catalog.
- 3 The pairings decide whether anyone clicks. The best add-ons are accessories, refills, protection plans, and matching pieces that cost less than the main product and obviously belong with it.
- 4 Shopify's free Search & Discovery app offers manual recommendations only. A dedicated FBT app adds order history analysis, one-click Add All to Cart, and per-pairing analytics.
- 5 The hybrid approach works best for most stores. Let the algorithm handle the catalog, then manually pin your top 10 products to their ideal partners.
- 6 Product page offers average a 7% acceptance rate across 66 million impressions on 250 Shopify stores. Track impressions, clicks, add-to-cart rate, and attributed revenue, and judge pairings by revenue, not clicks.
You have seen it a hundred times on Amazon. You look at a product, and right under it there is a small box that says "Frequently Bought Together." It shows two or three items that other customers bought in the same order, with one button that adds everything to the cart.
That little box is one of the most copied features in ecommerce. And you do not need Amazon's budget to get it. You can add the same system to your own Shopify store today, even if your store is small.
This guide shows you how to add frequently bought together on Shopify, step by step. You will learn how the algorithm behind it works, which products to pair (the part most guides skip), and what results to expect. We will also share real numbers from 66 million offers we analyzed across 250 Shopify stores.
Key Insight: Frequently bought together works because the suggestions come from real orders in your own store. That is why it feels like advice from other shoppers, not a sales pitch.
What Is Frequently Bought Together?
Frequently bought together is a product recommendation widget that shows items other customers bought in the same order. It usually sits on the product page, right under the main product details. Some stores call it "frequently purchased together," "Complete the Look," or "Goes Great With." Same idea, different label.
The widget works because of two things.
First, social proof. The suggestions come from real orders, so they feel like advice from other shoppers, not a sales pitch. Second, convenience. A good widget has an "Add All to Cart" button, so the customer grabs the extras with one click instead of hunting through your catalog.
Amazon made this format famous. Today, any frequently bought together Shopify app can give you the same system, sized for your store.
How the Algorithm Works
A real frequently bought together system does not guess. It reads your order history.
The algorithm looks at every completed order in your store and maps which products showed up together. When two products appear in the same order often enough, it pairs them.
Here is a simple example. Say 200 orders in your store contain running shoes. Of those 200 orders, 40 also contain performance socks, and 25 contain a shoe cleaning kit. The algorithm finds both pairings and ranks socks first, because socks show up more often.
Then it keeps learning. Every new order updates the math. A weak pairing at 100 orders can turn into a strong one at 300. New pairings appear as your catalog grows.
The Cold Start Problem
Here is the part nobody warns you about. If your store has fewer than 50 orders, the algorithm does not have enough data to find real patterns.
- Under 50 orders: pair products yourself.
- 50 to 100 orders: basic pairings start to appear.
- 200+ orders: the algorithm produces solid suggestions across your catalog.
If your store is new, start with manual picks and switch to the algorithm later. More on both modes below.
Warning: FBT algorithms need order data to work. If your store has fewer than 50 orders, start with manual product curation. Algorithmic pairings will not be reliable until you have enough purchase history.
What to Pair: The Part Most Guides Skip
Most articles tell you how to install the widget. Almost none tell you what to put in it. That is backwards. The widget is the easy part. The pairings decide whether anyone clicks.
Good pairings usually fall into four groups.
Accessories. Things that make the main product work better or last longer. A case for a phone. A strap for a camera. A cleaning kit for shoes. One warning: compatibility matters. A mount that fits this exact camera model is a great suggestion. A random mount is a returned order.
Refills and consumables. Things that run out. Coffee pods for a coffee machine. Filters for a water pitcher. Replacement heads for an electric brush. These pairings work well because the customer knows they will need more anyway.
Protection. Warranties, protection plans, and insurance-style add-ons. These fit higher-priced items like electronics and furniture, where a small extra fee protects a big purchase.
Completes the set. Matching pieces that finish a look or a kit. Earrings that match the necklace. The chairs that go with the table. This is where a "Complete the Look" title beats "Frequently Bought Together."
The quick reference version:
| If you sell... | Pair it with... | Why it works |
|---|---|---|
| Camera | Bag, memory card, strap | Needed on day one |
| Coffee machine | Pods, filters, descaler | Runs out, easy yes |
| Sneakers | Socks, cleaning kit | Small price, obvious fit |
| Sofa | Warranty, stain protection | Protects a big purchase |
| Dress | Matching bag, jewelry | Completes the look |
Two rules of thumb for any pairing. The add-on should usually cost less than the main product, so it feels like a small extra, not a second decision. And it should be obviously relevant. If you have to explain why two products go together, the pairing is wrong.
Tip: Not sure where to start? Open your last 20 orders and look at what customers already bought together. Your order history is the best pairing guide you have.
Shopify's Built-in Option vs a Dedicated App
Shopify has a free app called Search & Discovery. It lets you pick complementary products for each product page. Simple, and it costs nothing.
But it is not a true frequently bought together system. You choose every pairing yourself. No algorithm reads your order history. There is no one-click "Add All to Cart" button, and the analytics are minimal.
A dedicated frequently bought together Shopify app does the heavy lifting:
- Reads your order history and finds pairings automatically
- Lets you switch between automatic and manual modes
- Adds a one-click "Add All to Cart" button
- Gives you full design control, so the widget matches your theme
- Tracks impressions, clicks, add-to-cart rates, and revenue per pairing
| Feature | Search & Discovery | Dedicated FBT App |
|---|---|---|
| Pairing method | Manual only | Manual + algorithm |
| Order history analysis | No | Yes |
| One-click add all | No | Yes |
| Design customization | Basic | Full |
| Performance analytics | Minimal | Detailed |
If you are testing the waters, the free option is fine. If you want Amazon-style recommendations with real data behind every suggestion, you need a dedicated app.
How to Add Frequently Bought Together on Shopify (Step by Step)
The full setup takes six steps. You can finish it today.
Step 1: Check Your Order Count
Open your Shopify admin and look at your total orders. 50+ orders means the algorithm has enough data to start. 200+ means strong pairings across the catalog. Under 50, plan to start manually.
Step 2: Pick Your Mode
With enough order data, turn on algorithmic mode and let the system find pairings from real purchases. With a newer store, hand-pick 2 or 3 complements for each of your top sellers instead.
Step 3: Choose the Widget Title
"Frequently Bought Together" fits most stores. "Complete the Look" works better for fashion, decor, and lifestyle products. "Goes Great With" fits food and hobby stores. The title frames the suggestion, so match it to what you sell.
Step 4: Set Up the Widget
Show 2 or 3 products per suggestion. More than that, and people freeze. Add a clear "Add All to Cart" button. If you want a higher take rate, offer a small bundle discount, something like 5% to 10% off when bought together.
Step 5: Place It and Test It on Mobile
Put the widget below the main product details, near the buy button area. Shoppers who scroll that far are comparing options, so they are open to suggestions. Then check it on your phone. Most Shopify traffic is mobile, and a widget that is hard to tap will not get used.
Step 6: Launch and Wait Two Weeks
Go live, then leave it alone for at least two weeks. Early data is noisy and will push you into changes that mean nothing. Give the widget time to collect real numbers.
Key Insight: Start with your 10 best-selling products. Check the pairings the algorithm suggests, fix the ones that make no sense, then roll out to the rest of the catalog.
Manual or Automatic: Which One Should You Use?
This is the question every merchant asks. The answer depends on your numbers.
Go manual if you have fewer than 50 orders, a small catalog, or a curated brand where you want full control over every suggestion.
Go automatic if you have 100+ products, steady order volume, or a catalog too big to pair by hand. The algorithm also finds non-obvious pairings you would never guess on your own.
Or do what most established stores do: both. Let the algorithm handle the whole catalog, then manually pin your top 10 products to their ideal partners. You get scale from the algorithm and control where it matters most.
Tip: The hybrid approach works for most stores. Let the algorithm handle the catalog, then manually pin your top 10 products to their ideal partners. Scale and control at the same time.
Does It Actually Work? What 66 Million Offers Taught Us
Most guides stop at setup. We wanted to know what happens after, so we looked at the data.
We analyzed 66 million offer impressions across 250 Shopify stores, from January to June 2026. One caveat up front: our data groups offers by where they appear, not by widget type. So we cannot give you a number for FBT widgets alone. What we can tell you is how offers perform in the exact spot where frequently bought together lives: the product page.
| Where the offer shows | Average acceptance rate |
|---|---|
| Product page | 7% |
| Cart drawer | 12% |
| Checkout (Shopify Plus) | 9% |
| Post-purchase | 6% |
Product page offers get a "yes" 7% of the time on average. That may sound small, but the product page is your highest traffic spot by far. In our data, product page offers got 50 million impressions, more than every other spot combined. A modest rate on a huge number of views still adds up to real money.
Notice the cart drawer at 12%. Some stores show pairings there too, and it is the strongest spot we measured. If you want that side of the strategy, our cart drawer upsell guide covers it. (The checkout number comes from only 28 Plus stores, so treat it as a hint, not a law.)
One more honest note. Store to store, acceptance in the same spot swings from under 2% to over 20%. Your products, prices, and pairing quality decide where you land. Treat the average as a map, not a promise.
Our sample is 250 stores that actively work on their conversion, and the data is aggregated and anonymous. So read it as "stores that care about their numbers," not "every store on the internet."
What to Measure on Your Own Store
Track four numbers: impressions (how often the widget shows), click-through rate, add-to-cart rate, and attributed revenue. The last one matters most. A pairing with lots of clicks but few add-to-carts is showing the wrong product.
After the first month, swap your weakest pairings, test a different widget title, try a small bundle discount, and adjust the placement. Then repeat monthly. Keep your top 5 pairings, replace your bottom 5.
Warning: Track attributed revenue, not just clicks. A pairing with high clicks but low add-to-cart rates means the wrong product is being shown. Look at the full funnel: impression, click, add-to-cart, purchase.
How Growth Suite Handles Frequently Bought Together
Full disclosure: we make Growth Suite, and Frequently Bought Together for Shopify is one of its features. Here is what it does, so you can compare it with any other app.
Growth Suite analyzes your order history and finds pairings automatically, then keeps them updated as new orders come in. You can pin manual pairings on top, and your picks always win over the algorithm. The widget blends into your theme on desktop and mobile with no coding, and customers get one-click add to cart. Every pairing is tracked: impressions, clicks, add-to-cart rate, and revenue.
You can see how it stacks up against other tools in our honest comparison of the best Shopify upsell apps.
The Simple Version
Frequently bought together works because the suggestions come from real orders, not guesses. Start with your best sellers. Pair them with things that obviously belong together. Let the algorithm take over once your order history is deep enough. Then watch the revenue per pairing and keep improving.
The stores that win at this are not the ones with the fanciest widget. They are the ones with the best pairings.
7 Best Shopify Upsell Apps: Touchpoint Coverage Matrix Included
Over 100 upsell apps on Shopify. We compared 7 best across all 4 touchpoints with honest pros, cons, real pricing, and decision frameworks by goal, budget, and store size.
What if every discount went to the right person?
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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. He also wrote Growth Hacking'e Başlangıç (2015), a Turkish e-book on growth hacking, and its English edition, Introduction to Growth Hacking (2016).
Version History
Track updates and improvements to this article
Major update: added a new 'What to Pair' section covering accessories, refills, warranties, and compatibility. Added original research data from 66 million offer impressions across 250 Shopify stores, including product page acceptance rates. Rewrote the setup walkthrough from seven steps to six, added a definition section for first-time readers, and replaced unsourced CTR benchmarks with first-party data.
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