Frequently bought together is a common feature on Shopify stores, yet many fail to create a meaningful increase in order value. Poor product pairing, weak incentives, and untimely offers can limit results, even when the recommendations appear relevant. The real challenge is convincing shoppers to spend more is much harder.
Understanding why frequently bought together recommendations succeed or fail can help Shopify merchants build stronger offers, increase AOV, and generate more value from every order.
1. Understanding Frequently Bought Together
1.1 What Frequently Bought Together means
Frequently bought together means suggesting additional products that customers often purchase alongside the item they are viewing. Some recommendations come from past order data. Others are selected manually based on products that naturally work well together.
A store on Amazon introduces FBT bundles based on past order data.
Related product widgets are one of the most common recommendation features in ecommerce. Shoppers often see it on product pages, in cart drawers, inside add-to-cart popups, and sometimes during checkout.
🪑 For example, someone shopping for a dining chair may appreciate matching chair pads. A customer buying a facial serum may benefit from a cleanser and moisturizer that fit into the same skincare routine.
1.2 Frequently Bought Together and average order value
A frequently bought together widget increases AOV by motivating shoppers to add items they were not planning to buy. Three key factors usually make the biggest difference:
- Product relevance:The recommended item should support the main purchase. Accessories, replacement parts, consumables, and complementary products are especially effective because the connection is easy to understand.
- Timing: Add-ons work best when customers are already committed to the primary purchase. Recommendations shown too early or too late often receive less attention.
- Perceived value: Customers need a clear reason to spend more (e.g. convenience, savings,...)
1.3 Frequently Bought Together vs product bundles
Related product suggestions and product bundles can both increase order value, but they use different approaches. Think simply of it:
- An add-on section mainly acts as a suggestion. It mentions products that are often purchased with the current item and leaves the choice entirely for the shopper.
- Meanwhile, a product bundle is a complete offer with clearer value and stronger purchase motivation.
Imagine a camera store might use product pairing suggestions to introduce a memory card and camera bag. A bundle would package the camera, memory card, and bag together as a beginner photography kit.
2. How Frequently Bought Together can hurt Shopify stores
Many Shopify merchants assume cross-sell recommendations can only improve sales. In reality, poor recommendation strategies can create new problems across the shopping experience.
Distracting shoppers from the main purchase
Irrelevant suggestions compete for attention. Instead of moving toward checkout, shoppers may spend time evaluating products they never intended to buy.
Creating a cluttered page
Too many product cards, prices, badges, and buttons can make the page feel crowded. Necessary buying information becomes harder to find.
Reducing mobile usability
Mobile screens offer limited space. Large suggestion sections can push key content farther down the page. Buyers may need to scroll before reaching important actions.
Encouraging price comparison
Complementary products do not always boost buying intent. Some purchasers start comparing options and reconsider the order.
3. Why many Frequently Bought Together offers fail to increase AOV
A study reported that suggestion systems can increase conversion rates by 12% in online retail. However, many shop owners treat frequently bought together just as a recommendation feature instead of a meaningful offer. That's why this widget attracts attention without changing what customers buy. Several common mistakes below can limit results.
3.1 Reason 1: Recommendations create interest, not action
Forrester reports that 35% of US online adults consider related product sections an important feature on a retailer’s website. Many item-based recommendations look connected at first glance, but relevance alone rarely increases spending. Buyers may recognize the value of add-ons, yet still move forward without them. In most cases, the additional cost does not sound compelling enough right away.
Make the offer more compelling
Once paired with a clear incentive, related product widgets tend to be more persuasive. The right discount will turn interest into a stronger buying decision. Consider the following common options:
- Bundle discounts: Reward customers for purchasing related products together
- Tiered savings: Increase the discount as order value grows
- Quantity breaks: Offer better pricing when purchasers buy multiple units of the same item
- Free shipping thresholds:Motivate buyers to add one more product to unlock free delivery
Offer free shipping as an incentive for reaching cart spending conditions.
To discover how to turn a FBT function into a comprehensive bundling strategy, please check this article.
3.2 Reason 2: Buying now feels no better than buying later
When buying today offers no advantage over buying later, purchasers often delay the extra paying. Without a significant financial perk, adding more to the cart does not sound like a smart choice.
Give customers a reason to buy now
Customers should be able to understand why buying the items together is a better deal. Make the pricing breakdown easy to spot. Display the subtotal, bundle price, and savings amount near the call to action.
Effective bundle pricing also requires a balance between customer value and business goals. Discounts should support profitability while helping merchants move inventory and increase order value.
3.3 Reason 3: The recommendations do not solve a clear need
When product pairing suggestions appear random, even if the products have been purchased together in previous orders, shoppers still ignore them. Customers are far more likely to respond to recommendations that solve a specific need or support an achieve a clear outcome. The University of Florida study supports that recommendations help most when they improve search and value discovery.
Build bundles around real customer needs
Suggest accessory items to finish an oven setup. Show total price clearly.
- Build offers around clear use cases, such as “first apartment kitchen kit,” “home office starter set,” or “winter skin routine”.
- Group products that actually work together.
- Include accessories or supporting items needed to use the main product successfully.
- Create different combinations for beginners, enthusiasts, professionals, etc.
- Pair products with refills, maintenance items, or replacements customers are likely to need next.
3.4 Reason 4: The widget appears at the wrong moment
Someone who is still comparing sizes, colors, or product features is often focused on choosing the main item. Extra products, even a well-matched offer at that stage, can be overlooked. Instead, wait until buyers have committed to the primary purchase.
Match the deal to the buying journey
Choose the right placement for diverse types of bundle offers to not disrupt checkout path.
- Product pages: Work well for bundles that require more consideration, such as outfits, skincare routines, starter kits.
- Cart drawers and cart pages: Often perform better for accessories, refills, warranties, and other small add-ons.
- Checkout offers: Best suited for low-cost extras that customers can accept without comparing multiple options.
Jones Road Beauty suggests related items in multiple steps: product page, cart drawer, and checkout page.
3.5 Reason 5: The suggestions replace a better purchase
Frequently Bought Together does not always generate additional demand. Sometimes it encourages shoppers to choose a lower-margin option instead of a more profitable purchase. The final cart may still contain more items, yet the business may earn less from the sale.
Measure profit, not just revenue
To understand the true impact of bundle recommendations, evaluate revenue metrics alongside profit metrics:
- Gross margin: Measure how much profit remains after product costs.
- Discount cost: Track how promotions affect the profitability of each order.
- Product mix: Review whether recommendations are shifting demand toward lower-margin products.
- Contribution profit: Evaluate how much each recommendation contributes to overall business performance after costs and discounts.
4. How to track performance of cross-sell recommendations?
Higher AOV can be a positive signal, but it does not explain why performance changed. The metrics below can help reveal whether a product bundle suggestion is truly successful.
Among these metrics, attach rate is often the easiest place to start. Low attach rates usually indicate that shoppers do not find the recommendation compelling enough to add another product to their order.
Conclusion
The most effective frequently bought together recommendations are built around customer decisions. Do not try to show more items. Instead, motivate buyers gently to add products they were likely to want together in the first place.
Frequently asked questions
1. Does frequently bought together increase average order value?
Frequently bought together can increase average order value when the recommended products genuinely encourage customers to spend more. Simply showing related products does not guarantee larger orders. Success usually depends on product relevance, clear savings, and good timing.
2. What is the difference between frequently bought together and product bundles?
Cart add-on suggestions recommend products that are often purchased together. Bundles combine selected items and offer bundle pricing or savings. As a result, bundling usually provides a stronger reason to buy multiple items at once.
3. Why do shoppers ignore frequently bought together recommendations?
Many shoppers ignore recommendations when the suggested products do not seem relevant to their needs. They are less likely to engage with product suggestions when the value is not immediately obvious.