20+ Product recommendation examples & strategies to boost AOV

With Amazon generating 35% of its revenue through its recommendation engine, it is clear that personalized suggestions are essential for growth. The reality is that shoppers abandon sites not due to a lack of options, but because they feel overwhelmed by the sheer volume of choices.

You can fix this decision paralysis with product recommendations, which are automated suggestions that filter items based on user behavior or product features. This guide will explore 20+ product recommendation examples that you can implement to drive more revenue.

How does product recommendation work?

Most recommendation engines rely on 3 core methods to predict what a customer wants. Here is a simple breakdown of how they operate.

Collaborative filtering

This method relies on the “wisdom of the crowd.” Instead of analyzing the product itself, the system looks at the behavior of thousands of other shoppers. For example, if data shows that people who bought a specific book also purchased a highlighter, the system learns this pattern. When you add that book to your cart, it suggests the highlighter because so many others have done the same.

Content-based filtering

This approach ignores what others are doing and focuses solely on the product’s “DNA.” It analyzes specific attributes such as color, material, and keywords. If you are viewing a white linen shirt, the system identifies traits like “linen” and “white.” It then suggests other products with the same properties, assuming you want more items with that specific style or fabric.

Hybrid systems

Hybrid systems combine the strengths of both methods to deliver the most accurate results. By combining crowd data with product attributes, this approach addresses the blind spots of relying on a single method. It can suggest an item that is currently trending (Collaborative) while ensuring it still matches your specific color or style preferences (Content-Based). This dual capability is why sophisticated AI product recommendations are the key to boosting e-commerce sales for growing brands.

Common types of product recommendation systems

Recommendation type	How it works	Best used for
1. Rule-based	Suggestions follow the store owner’s “if-this-then-that” logic (e.g., “Always show belts with pants”). It relies on static attributes, such as categories or tags, rather than learning from user actions.	New stores with low traffic, simple cross-sell bundles, promoting specific inventory
2. Behavior-based	This system tracks actions like product views, clicks, and cart additions to identify intent. If a user keeps browsing running shoes, the site adapts to show more athletic gear in real time.	Medium-to-large stores, “Recently viewed” sections, dynamic category pages
3. Personalized	The most advanced method uses AI to create a unique experience for every individual. It combines historical data with real-time context to predict exactly what a specific user is likely to buy next.	High-volume retailers, 1:1 email marketing, custom homepage feeds

Product recommendation examples by placement

Homepage

The homepage serves as the primary routing hub for your store, where visitors arrive with widely varying intents. To keep them from bouncing, your recommendations must function as dynamic signposts that immediately reduce cognitive load. Here are 4 essential strategies to shortcut the discovery process and guide users into high-converting funnels.

Best sellers

Best Sellers are essentially a safe entry point for new visitors who lack brand trust. By showcasing verified winners, you leverage social proof to tell undecided shoppers that these items are safe bets because others are buying them. This strategy is most effective for first-time visitors who need a shortcut through your catalog to avoid decision fatigue.

A standout example is A.P.C., which takes a unique approach by presenting best sellers as an interactive overlay rather than a static grid. Instead of waiting for the user to scroll and find a section, this widget proactively interrupts the browsing experience to offer a curated menu of hits, ensuring the most popular products are impossible to miss.

Trending now

While best sellers represent long-term popularity, “Trending Now” captures immediate excitement and high-velocity sales. This tactic works by triggering the “fear of missing out” (FOMO), signaling to customers that these items are having a moment and might sell out soon. It is particularly powerful during seasonal shifts or viral spikes when you want to capitalize on impulse buying behavior.

SodaStream executes this perfectly with their “Check out what’s trending now” carousel. By isolating specific flavor bundles and hot machines, they guide customers toward relevant, timely purchases rather than overwhelming them with their entire hardware lineup.

New arrivals

The “New Arrivals” section serves as a retention engine for returning customers who are already familiar with your core inventory. These shoppers need a dopamine hit of novelty to engage, making this placement crucial for keeping your store feeling fresh and dynamic. It should be prominent for logged-in users or repeat visitors who are looking for their next purchase.

Super Smalls demonstrates this well with a vibrant “What’s New” section that visually distinguishes itself from the rest of the page. By placing this front and center, they ensure loyal fans see the latest jewelry drops immediately, preventing them from assuming the catalog hasn’t changed since their last visit.

Quiz-based

This strategy asks users a few simple questions to understand their needs, then generates a custom list of recommendations. It works because it replaces the frustration of guessing with a tailored solution, giving shoppers confidence that they are buying the right product. You should use this for complex categories like skincare or vitamins, where people often feel overwhelmed by choices.

Davines does this beautifully on their homepage with a “Find Your Perfect Haircare Routine” prompt. By answering questions about hair texture and goals, the user receives a specific regimen, making the experience feel like a truly personalized customer experience rather than a generic search.

Product use cases

This approach groups recommendations by activity or purpose rather than by standard product categories. It is effective because it aligns with how customers actually think about their problems, helping them find solutions without needing to know technical product names. This is ideal for functional brands where performance matters more than style.

Bombas uses this perfectly on their homepage with a section called “A Sock for Every Occasion.” Instead of a grid of socks, they organize them by activities like Running, Hiking, or Dress. This simple layout lets users instantly find the right gear for their lifestyle without sifting through dozens of similar options.

Collection page/Category page

Once a visitor enters a collection page, they have declared their intent, but often face an overwhelming “wall of products.” Your goal here is to act as a smart filter, helping them save time and prevent decision fatigue. Here are 2 effective examples to guide these high-intent shoppers using crowd data and expert authority.

Most popular (in this collection)

This tactic highlights best-selling items specifically within the current category rather than across the whole store. It works by instantly flagging the safest choices for that specific product type, which uses social proof to reduce purchase anxiety. This is best placed at the top of category pages to help users identify top performers immediately.

Böhme uses this effectively with a carousel above their product grid. Before a shopper scrolls through hundreds of dresses, they see the styles other customers love most, allowing undecided buyers to find a safe option without manually filtering.

Expert/staff picks

This strategy features products selected by your team or industry professionals. It builds trust by replacing cold data with human authority, which is crucial for high-value or niche items that need more than just popularity to sell. Use this for luxury goods or technical equipment where expert opinion carries weight.

Clark’s Botanicals elevates this by labeling items as “Editor’s Favorites” and pairing them with badges from magazines like Vogue. This third-party endorsement signals quality and assures customers that these products are worth the premium price.

Product detailed page (PDP)

Once a shopper lands on a product page, they are in the consideration phase. Your goal now shifts from broad discovery to specific cross-selling or saving the sale. You need strategies that confirm their choice, offer alternatives if they hesitate, or increase the order value before they hit checkout. Here are five powerful ways to do that.

Similar products

This section suggests alternatives that share features or price points with the current item. It saves the sale when a customer likes a product but has a specific objection, offering an immediate backup plan so they don’t leave. This is essential for out-of-stock items or categories with many style variations.

Sephora improves this by using a comparison table. They line up similar products with key specs, such as ratings and ingredients, side-by-side, empowering users to make quick trade-off decisions without opening multiple tabs.

Frequently bought together

This approach identifies essential add-ons commonly purchased with the main item. It removes friction by anticipating needs, making it easier to buy a complete solution than a single product. This is perfect for electronics or items that require accessories.

Walmart executes this well with its bundle widget for gaming consoles. When viewing an Xbox, the site presents a pre-checked bundle with a controller and a game. The single “Add all to cart” button makes it effortless for the customer to increase the order value. By turning a simple purchase into a full package deal, brands can effectively maximize customer value during a single visit.

Complete-the-look sets

This visual strategy recommends matching items to create a cohesive outfit or room. It helps customers visualize how to style a product, which builds an emotional connection and encourages them to buy the whole set. This is critical for fashion and home decor brands.

Meshki demonstrates this by showing the exact bag and heels worn by the model next to the dress. The matching aesthetic reinforces that these items belong together, making the upsell feel like helpful styling advice.

Complementary products (accessories)

This tactic suggests low-cost items that enhance the main product, such as cleaners or batteries. It works because these add-ons protect the customer’s investment, making the decision low risk. Use this for leather goods or gadgets where maintenance is a concern.

WP Standard uses this subtly by suggesting a leather cleaner when you view a tote bag. Positioned near the footer, it feels like a practical care tip rather than a sales pitch, making it an easy addition for the buyer.

People also bought

This section shows what other customers purchased in similar sessions. It relies on community trends to validate choices, telling the user that a combination is trusted by their peers. This is best for trendy items where social proof drives discovery.

ASOS uses this effectively by suggesting matching bottoms for a beach top based on purchase data. This data-driven approach eliminates guesswork and gives shoppers confidence that they are making a popular choice.

Cart & checkout

The checkout process is the final hurdle. At this stage, the customer has already decided to buy, so your goal is to increase the order value without distracting them or causing cart abandonment. The key is to offer low-friction additions that feel helpful rather than pushy.

Free shipping nudges

This example uses a dynamic progress bar to show customers exactly how much more they need to spend to qualify for free shipping. It works because it gamifies the shopping experience and frames the extra purchase as a way to “save” money on shipping fees. You should use this in the slide-out cart or at the top of the checkout page.

Velour effectively conveys this message by displaying “You’re Only $27 CAD Away From Free Shipping!” directly above a row of low-cost product recommendations. This prompts the user to add a small item, such as tweezers or lash adhesive, to hit the threshold, turning a shipping cost into a product purchase.

Impulse add-ons

These are low-cost, high-utility items that customers can add to their cart with a single click, without much research. It works on the same principle as the candy racks at a grocery store checkout; grabbing a small “treat” feels effortless. Use this strategy for consumables, samples, or travel-sized versions of your best sellers.

Beekman 1802 does this well in their slide-out cart. They highlight a “Great Deal!” on a small body bar set, making it easy for customers to toss it in at the last minute. The low price point means it doesn’t require a big decision, making it an easy AOV booster.

Services/Warranties

This tactic offers non-physical add-ons like extended warranties, shipping protection, or personalization services. It works because it addresses post-purchase anxiety (What if it breaks? What if it gets lost?) for a fraction of the product cost. This is essential for jewelry, electronics, or high-value furniture.

Jens Hansen uses this brilliantly for their Lord of the Rings rings. Right in the cart, they ask, “Would you like to add Elvish Inscription Checking Service?” For a $2,000 ring, a $20 service fee feels negligible to ensure the engraving is perfect. It adds value and peace of mind without cluttering the cart with physical products.

Email & on-site messaging

The customer journey does not end when a visitor leaves your site. Whether they bought something or just browsed, sending the right message at the right time brings them back. This section focuses on re-engaging users through their inbox and proactively guiding them with smart onsite triggers.

Browse abandonment recommendations via email

This strategy targets visitors who viewed products but did not purchase. It works by reminding them of what they already liked, removing the friction of having to search for it again.

National Mattress executes this well with a personalized email. The subject line “Consider This A Sign!” grabs attention, while the body simply shows the exact mattress the user viewed. By focusing purely on the product they were already considering, they make returning to the cart easy and inviting.

Post-purchase follow-ups via email

Once a customer buys, they are primed to engage again. Post-purchase emails shouldn’t just be receipts. There is a chance to offer complementary items.

Pattern Brands uses this to inspire rather than just sell. Their “Ready, Set, Routines” email frames cross-sells as lifestyle upgrades, suggesting a French Press or Entryway Rack to build better habits. This turns a simple product recommendation into a helpful guide for living better, which effectively helps to increase customer lifetime value over time.

Contextual assistance (on-site chat)

Customers often get lost in large catalogs with complex specs. Instead of forcing them to use filters, an AI chat can instantly find the right match based on their specific needs.

Decathlon used Chatty to help shoppers navigate 10,000+ items. When a user asked for “a tent for alpine weather,” the AI didn’t just search keywords. It understood the requirement and recommended the exact model built for those conditions. This real-time guidance shortcuts the search process, helping customers find what they need instantly.

Expert verification (onsite chat)

For technical or high-ticket items, customers often freeze at checkout because they aren’t sure if a part fits. On-site messaging can solve this by confirming compatibility on the spot.

Yoeleo Bike used Chatty to verify purchases for cyclists spending $999 on wheels. Instead of guessing, customers could ask the chat widget to confirm bearing compatibility with their specific bike frame. The AI provided an instant green light, giving shoppers the confidence to click “Buy” immediately rather than abandoning the cart to do more research.

404 pages

A 404 error page is traditionally a dead end where traffic bounces. However, smart brands treat it as a hidden landing page. Instead of just an apology, this page should be a “recovery vehicle” that re-engages lost visitors by offering them a new path forward, turning frustration into discovery.

Gamified discovery

This strategy uses interactivity to soften the annoyance of a broken link. While not a direct product grid, it recommends a “brand experience” to keep the user engaged long enough to click “Shop” again. It works because it disrupts negative friction with a moment of delight.

Tattly does this brilliantly by offering a “hidden Tattly” (random tattoo design) when you hit a 404. It turns a mistake into a slot-machine-style game. By piquing curiosity, they prevent the user from closing the tab, subtly guiding them back to the main catalog to find the real version of the “magic” they just saw.

Curated collection rescue

When a specific product link fails, the next best thing is to recommend a highly curated selection that matches the user’s likely taste. It works by assuming that if the user is lost, they need a “safe” suggestion to get back on track.

Ted Baker executes this with a “A chosen few you’ll love” section at the bottom of their 404 page. Unlike a generic “back to home” button, this widget proactively surfaces specific, high-quality items (like a coat or earrings). It acts like a personal shopper, saying, “Sorry that item is gone, but we think you’ll really like these instead.”

Crowd-sourced bestsellers

Sometimes, the most effective way to save a sale on a 404 page is to show what everyone else is buying. This strategy leverages social proof to present the most popular items as a fallback. It works because it reduces decision fatigue. If the user doesn’t know where to go, the “crowd” directs them.

Urban Outfitters uses this effectively by displaying a “Most Popular” grid directly under their error message. By showcasing high-converting items like fleece jackets and backpacks, they turn a broken link into an opportunity to discover the store’s top hits.

When not to use product recommendations

While recommendations are powerful, they can backfire if used incorrectly. Here are 4 scenarios where you should limit or avoid automated suggestions.

• When your catalog is too small: If you only have a few products, algorithms will just repeat items the user has already seen. In this case, manual bundles or a simple “Shop All” link work better than repetitive widgets.
• When behavioral data is insufficient: New stores often lack the traffic needed for “People also bought” engines to work accurately. Relying on sparse data leads to irrelevant suggestions, so it is safer to stick to manual “Staff Picks” until your volume grows.
• When it causes decision fatigue: Bombarding users with too many widgets (e.g., New, Trending, and Similar all at once) creates cognitive overload. If customers face too many choices, they are more likely to leave than to buy.
• When it breaks the context: Showing low-cost impulse items on a high-end luxury product page or irrelevant ads on a “Support” page can damage trust. Recommendations must always match the user’s current goal to avoid feeling like spam.

Best practices for effective product recommendations

To maximize conversions without annoying your customers, follow these five practical rules for your recommendation widgets.

• Limit suggestions to 4-6 items: Keep it clean. Showing more than six items typically causes choice overload, making users less likely to click anything at all.
• Prioritize relevance over personalization: Context matters most. If a customer is viewing winter boots, show them wool socks, even if their past history says they like sandals. Always match the current session’s intent first.
• Filter out purchased items: Don’t waste valuable screen space showing customers what they already own. Configure your logic to automatically exclude items from their recent order history.
• Add social proof to widgets: Increase trust by displaying star ratings or “Top Rated” badges directly on the recommended product cards. A 5-star review count makes a suggestion feel like a verified tip rather than just an ad.
• A/B test everything: Never assume a strategy is perfect. Continuously test different locations (e.g., cart vs. checkout) and widget titles to see which variation actually drives more revenue.

Final thought

Bottom line: adding smart suggestions is one of the easiest ways to increase your store’s revenue without needing more traffic. We’ve covered a lot of ground, but even implementing just two or three of these product recommendation examples can make a massive difference. Trust the process, keep testing, and happy selling!

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