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We are a team of passionate individuals, all driven by a singular goal - to help our merchants succeed.
We recently went out to buy a coffee maker for our team here at Skai Lama. Having little to no knowledge of coffee makers, we were feeling a bit lost. Naturally, we turned to the salesperson who helped us find the best fit and even the accessories needed to complete our coffee station.
At that moment, it made sense to us why e-commerce giants like Amazon to fashion retailers like H&M are heavily prioritizing frequently bought together recommendations. For online stores that can't have a salesperson dedicated to each customer, these recommendations bridge the gap by offering the same level of personalization and convenience.
The impact of such product recommendations is so much so that up to 35% of sales on major e-commerce platforms like Amazon come from recommended products.
Engaging with just one product recommendation can increase a customer's average order value (AOV) by 369%.
So, it’s clear that product recommendations can be a powerful sales driver. However, not all product recommendations work this way.
Generic suggestions can do the exact opposite. They can confuse customers, waste their time, and ultimately turn them away. In that case, implementing a frequently bought-together system can do more harm than good.
Only when the product recommendations are personalized and take into account the customer's browsing history, past purchases, and even inferred needs, can they truly be effective. In fact, a whopping 66% of customers expect nothing less and will only become repeat customers if they receive a personalized experience.
Having a smart and personalized frequently bought-together system pays off, not just for increased sales, but for customer satisfaction as well.
Studies show that 71% of consumers report feeling frustrated when their online shopping experience fails to offer personalized product recommendations. By implementing a system that suggests relevant, complementary products, you can streamline the shopping journey, reduce decision fatigue, and ultimately create a more positive customer experience.
In this blog, we’ve laid out the best frequently bought-together examples that can inspire your own "Frequently Bought Together" section.
Frequently bought together is a feature commonly found on e-commerce platforms, particularly on product pages.
When you're shopping for a product online, let's say a laptop, you must have seen a section below the product description labeled "Frequently Bought Together." In this section, you'll typically find other items that customers buy along with the laptop, such as a laptop bag, a mouse, or a laptop stand.
It’s a highly effective way to improve the shopping experience and the AOV by suggesting complementary and relevant products based on past purchasing patterns and customer behavior.
When it comes to product recommendations, Amazon is really the king. After all, 35% of Amazon's sales come from their recommendation engine. This dominance isn't just a coincidence though; it's the result of really clever algorithms, data, and a relentless focus on personalization.
From frequently bought together items to products related to past purchases and browsing history, Amazon's recommendations feel eerily in tune with our needs and desires. Don’t they?
Think about the last time you purchased a string of suggested items that seemed to magically complete your shopping list.
See how we added a foundation brush, and suddenly we’re given recommendations for a row of items like foundation, concealers, setting powders, and even a handy makeup sponge.
It's almost like Amazon can read your mind.
In fact, the minute you add something to your cart, a Frequently Bought Together section appears displaying other products people often buy with that item.
⬆️ Check out the image above. See how there's a section right next to the cart titled "Pair with your cart"? This goes beyond simply suggesting frequently bought-together items. It personalizes the recommendations based on the specific items already in your cart.
Amazon also uses a “Customers who viewed this also bought” section to help customers find new products that they might be interested in, especially if they are browsing for something specific and want to see what other people have bought along with it. For example, when buying a moisturizer on Amazon, the Frequently Bought Together section suggested sunscreens.
Amazon takes personalized product recommendations even a step further by suggesting items inspired by the wish list. This caters to the aspirational shopper in all of us.
Now, let’s say you didn’t make a purchase and kind of abandoned your cart. However, every time you come back, Amazon lets you start your shipping journey from right where you left off. From “Keep shopping for” to “Deals inspired by your recent history”, see how I’m presented with multiple options to resume buying: ⬇️
Safe to say, Amazon's Frequently Bought Together (FBT) feature is a goldmine for both customer convenience and increased sales. It is a masterclass in suggestive selling that other D2C brands can definitely learn from and adapt. By implementing a data-driven FBT strategy, D2C brands can create a win-win situation: offering a more convenient shopping experience for their customers while boosting their own sales potential.
Want to know how to boost sales with effective product bundling strategies?
There's a reason why Sephora is the top destination for beauty enthusiasts. From fun quizzes to personalized picks, they've perfected the art of making beauty shopping an engaging and highly personalized experience.
Similar to Amazon's Frequently Bought Together feature, Sephora suggests complementary products alongside the one you're viewing.
For instance, when we added a blush to our cart, the "We Think You'll Also Love" suggested a compatible blush brush, liquid blush, and even a lip oil for a complete makeup look.
This tailored Frequently Bought Together function is what sets Sephora apart – they don't just suggest random add-ons, they curate recommendations that complement your chosen product and potentially inspire a complete look. It feels similar to having a makeup artist by your side, helping you create the perfect beauty routine.
Sephora's personalized touch extends beyond the website. They leverage purchase history and browsing behavior to send targeted emails like "Shop Our Picks For You."
How would you like to receive an email featuring a blush you recently viewed, alongside a perfectly matched lip balm and a trendy concealer? Well, 76% of you love it, so we are guessing, elated.
These Frequently Bought Together email suggestions consider your past interactions and curate enticing product combinations you might not have thought of before.
This, in turn, not only reminds you of products you've shown interest in but also tempts you to discover new favorites, solidifying Sephora's position as your go-to destination for all things beauty.
But Sephora doesn't stop there. They understand that navigating so many beauty products can quickly get overwhelming. So, instead of suggesting a Frequently Bought Together recommender, they curate a sophisticated "Pick Up Where You Left Off" section on the homepage. This section remembers your browsing journeys and shopping cart content, offering a variety of ways to resume your shopping journey.
Curious about the best bundling strategies for beauty and cosmetic brands?
Bershka takes a refreshingly focused approach to Frequently Bought Together recommendations. Instead of showing various options, Bershka prioritizes helping customers complete their look.
If someone has set their heart on a stunning dress. Bershka's FBT engine understands the struggle of finding the perfect matching shoes, bag, or jacket. And it acts on it by removing the need for frantic searching by intelligently suggesting complementary pieces.
Now, everything you need to look put together is presented right there, reducing decision fatigue and potentially increasing your basket size.
Instead of selling just ‘clothes’ that every other brand does, Bershka focuses on selling looks acting as your personal fashion stylist.
Also, notice how cleverly the Frequently Bought Together recommender sneaks in a discounted deal on the suggested item to sweeten the pot. If the customer isn't already convinced by the curated look, this strategic placement of a sale price adds an extra layer of temptation.
Now, right at the checkout window, you would see another FBT section titled "You Might Be Interested In." By placing complementary accessories here, Bershka capitalizes on a moment of high purchase intent.
Think about it - you've already committed to buying the dress and are about to finalize your purchase. Suddenly, you see a pair of sunglasses or a statement necklace that perfectly complements your chosen outfit. The effort of searching for these items has been eliminated, and the timing is perfect – you're already in the buying mood. This "You Might Be Interested In" section acts as a last-minute impulse buy trigger, potentially increasing your basket size even further.
Pro-tip: Don't be afraid to showcase unexpected pairings or trending styles when giving "lookalike" suggestions. This can spark inspiration and encourage customers to step outside their comfort zone, leading to exciting fashion discoveries.
Looking for creative ways to bundle clothing items for fashion retail?
Velotric, an e-bike company, focuses on creating value for the customer with its Frequently Bought Together function.
When you add an e-bike to your Velotric cart, their FBT engine intelligently recommends bundle offers that combine the bike with frequently purchased items at a discounted price. Now, who wants to miss out on a good deal? The potential loss of that bundled discount can be a powerful motivator to hit that "purchase" button.
Also, by showcasing the discounted bundle price, they subtly influence your perception of the individual items' value. Even if you don't go for the bundle, you might be more likely to purchase separate accessories because the initial bundled price creates a more attractive reference point.
What we particularly liked about Velotric’s Frequnetly Bought Together engine is its approach to suggesting add-on accessories. It doesn't simply push the most expensive items.
Instead, the FBT system recommends a lower-priced, essential accessory alongside it. This targeted recommendation caters to the customer's initial investment, potentially nudging them towards a well-rounded purchase experience without overwhelming them with expensive extras. It's a smart way to encourage additional spending while remaining mindful of the customer's budget.
Velotric’s FBT engine pushes the customer one last time during the checkout. Having the accessories readily available right when the customer is most engaged with the e-bike purchase creates a sense of "might as well" or "why not?" It reduces the mental hurdle of actively seeking out those accessories later, potentially leading to impulse purchases or a feeling of incompleteness if they don't add them.
Pro tip:
Boll & Branch takes a proactive approach with their "Frequently Bought Together" engine. They don't wait until the customer reaches the final stage; they engage them right from the browsing stage.
And mind if we say, they are smooth with it.
If you’re browsing a luxurious Boll & Branch sheet set, a subtle "Pairs Well With" section shows up alongside the product description. This curated selection doesn't bombard you with random add-ons; instead, it showcases complementary items like plush blankets or comfy pillows.
Why would that work though?
Mainly because in the initial browsing phase, customers are often open to exploring complementary products. They haven't yet solidified their purchase decision, making them more receptive to suggestions that might enhance their overall experience.
Lastly, at checkout, they introduce a strategic deal – Add & Save 10%. The "Add & Save 10%" offer sweetens the deal, making it feel like you're missing out on a good bargain if you don't add these items. This final nudge towards a more complete sleep experience capitalizes on the customer's commitment to purchase and the potential for additional savings, ultimately increasing Boll & Branch's average order value.
Overall, Boll & Branch's early engagement FBT strategy is a clever way to nudge customers towards a more complete and potentially more expensive purchase.
Wondering how to implement effective product bundling for home textiles?
West Elm, an online furniture retailer, takes a multi-layered approach to their Frequently Bought Together strategy.
Let’s say you’re browsing sofas. West Elm doesn't limit their frequently bought-together suggestions to the same category.
Instead, their FBT engine recommends coffee tables, armchairs, or even lamps from different categories. They play on the concept of room completion. By recommending frequently bought together items across different categories, they subtly nudge customers towards building an entire living space, potentially leading to a larger purchase.
West Elm also leverages social proof by showcasing best-selling items within the "Also in this collection" section.
This is actually a very clever FBT tactic. In e-commerce where customers can't touch, feel, or try on the products, they are more likely to trust and be influenced by popular choices. Especially when it comes to expensive and one-time buys like a sofa or bed.
The absence of physical interaction creates a layer of uncertainty for customers. Highlighting best-selling items in this context provides much-needed validation and acts as a trusted voice.
It precisely conveys: "If so many others are choosing this sofa, it must be good," reducing the perceived risk associated with a high-value purchase. This strategy becomes even more powerful for expensive and infrequently bought items like sofas or beds.
Did you know more than 64% of customers wait to buy a product until they see a discount?
Again, West Elm gets it and of course, they don't miss the opportunity to feature limited-time discount deals to nudge those indecisive customers towards a purchase. Their "People also Browsed" section strategically highlights limited-time discounted items, playing on the fear of missing out (FOMO) and creating a sense of urgency. This Frequently Bought Together tactic can be highly effective in converting browsers into buyers, especially for those who are price-conscious or who thrive on the thrill of a good deal.
Want to see how bundling strategies can work for furniture retailers?
Customers crave a shopping experience that feels tailored to their unique preferences. Perhaps that's the reason why almost 74% of eCommerce brands have some sort of a personalization program. That translates to as much as 40% more revenue.
Are you part of that lot? If not, you might be missing out on a significant chunk of revenue. Today's consumers expect a shopping experience that feels personal, and personalization programs can deliver just that.
But where do you begin? Building a recommendation engine from scratch can be overwhelming. That's where Skailama can help. Fly by Skai Lama is a powerful tool that empowers Shopify merchants to create strategic product bundles and personalized FBT recommendations.
Home furnishing retailer Bechester, for instance, leverages Fly to personalize their product recommendations & volume-based FBT bundles to nudge customers towards complementary items.
So, let's say if you're browsing a mattress, you would probably see a ‘Complete Sleep Package’ alongside the mattress, containing items frequently purchased together like a supportive pillow, a breathable mattress protector, or even a set of crisp sheets – all bundled at a discount. By offering these convenient bundles, Bechester increases it's average order value, improves conversion rates, and keeps customers happy with a one-stop sleep solution.
From cross-selling complementary products to suggesting upgrades and discounts at checkout, Skai Lama can help you effectively integrate frequently bought-together recommendations in your Shopify store.
Ready to take your Shopify store to the next level?
We are a team of passionate individuals, all driven by a singular goal - to help our merchants succeed.