Top Product Recommendations Examples That Drive Conversions

Product recommendations examples play an important role in the success of any eCommerce store. By showcasing the right products at the right time, these personalized suggestions not only help meet customer expectations but also foster loyalty, enhance satisfaction, and boost average order value. 

In this article, we will explore the most effective product recommendation strategies. We’ll examine real-world examples from top brands to show how personalized recommendations can drive sales and improve the overall customer experience.

Let’s dive in!

What Exactly Does “Product Recommendations” Mean?

Product recommendations refer to personalized suggestions made to customers, often based on their browsing behavior, past purchases, preferences, or demographic data. These recommendations help guide users to relevant products, improving their shopping experience and increasing the likelihood of additional purchases. 

Product recommendations appear on product pages, email campaigns, or during checkout. They are designed to enhance customer engagement, drive conversions, and increase sales for an ecommerce store.

Product Recommendation Examples You Can Apply

Here are examples from real-world brands to inspire your product recommendation strategy:

Recently Viewed Items

When a shopper visits a product page, it signals potential interest in purchasing, even if they are still in the research phase. By reminding customers of the items they’ve recently viewed, you can effectively reignite their interest and encourage them to complete their purchase. This simple yet powerful strategy helps boost conversion rates by bringing relevant products back into the customer’s focus.

Real-World Example: 

Etsy displays a “Recently Viewed” section on its product pages, helping users quickly find items they’ve previously looked at. This not only simplifies their shopping experience but also increases the chances of a return visit and purchase.

You May Also Like

The “You May Also Like” recommendation strategy suggests products related to the current item being viewed, often based on category, style, or other relevant attributes. This approach keeps customers engaged by showing them additional products they might find appealing, which can lead to increased conversions and higher average order values.

Real-World Example: 

eBay utilizes the “You May Also Like” feature by recommending similar products or items from the same category when a customer is viewing a product. This suggestion appears below the product description, allowing users to discover related items that may interest them easily.
 

Bought Together

The “Bought Together” recommendation strategy suggests complementary products that are frequently purchased together with the item a customer is currently viewing. This cross-selling technique is effective in increasing the average order value by encouraging customers to buy related items they might need alongside their original selection.

Real-World Example:

Flipkart uses the “Bought Together” feature to recommend accessories or complementary products when a customer views an item. For example, if a user is browsing a laptop, Flipkart may suggest a laptop bag, a mouse, or external storage devices that are commonly bought together with laptops. These suggestions appear near the product description or in the cart, making it easy for customers to add related items with just one click.

Similar Products

The “Similar Products” recommendation strategy suggests items that are alike in style, category, or attributes to the product the customer is currently viewing. This helps customers discover alternative options that might meet their needs or preferences, often leading to more conversions by giving them choices within the same product category.

Real-World Example:

Myntra employs the “Similar Products” strategy by displaying items similar in style or design to the one the customer is currently browsing. For instance, if a user is viewing a pair of sneakers, Myntra will show other sneakers with similar designs, colors, or brands. This allows customers to explore more options within the same category, increasing the chances of a sale.

Based on Your Browsing History

The “Based on Your Browsing History” recommendation strategy suggests products to customers based on the items they have previously viewed. This strategy leverages the power of user behavior to provide personalized recommendations, helping to keep customers engaged by showing them products that align with their interests, increasing the likelihood of future purchases.

Real-World Example:

Amazon uses the “Based on Your Browsing History” strategy to recommend products related to those a customer has previously looked at. For example, if a customer has been browsing for smartphones, Amazon will display related items such as phone cases, chargers, or other accessories. 

Highlight Bestsellers

The “Highlight Bestsellers” recommendation strategy showcases the most popular products on your website. By displaying items that are widely purchased or highly rated by other customers, this strategy leverages social proof to encourage new customers to consider these products, increasing the likelihood of conversions.

Real-World Example:

Amazon prominently features “Bestsellers” in various product categories, such as electronics, books, and home goods. For example, when browsing for books, Amazon will display a list of best-selling titles in that genre, often with customer ratings and reviews. This encourages customers to explore popular products that other shoppers trust, helping to drive sales.

Recommendations Based on Product Use Cases

Sometimes, recommending products based on specific use cases is more helpful for customers than simply suggesting individual items. By categorizing products based on their intended use, such as “running socks,” “office wear,” or “winter gear”, customers can quickly find what they need without having to browse through numerous options.

Real-World Example: 

Bombas uses the “Recommendations Based on Product Use Cases” strategy effectively. When browsing their socks collection, customers can choose from specific categories such as “athletic socks,” “dress socks,” or “socks for lounging.” This approach helps customers quickly find the right products for their needs, whether they’re looking for socks for running, casual wear, or specific occasions.

New Releases

By featuring new Releases, online stores can highlight the latest products, attracting customers interested in exploring new trends. This strategy not only makes the store feel dynamic but also encourages repeat visits as customers return to check out the latest items in various categories.

Real-World Example: 

Amazon uses a “New Releases” section across multiple categories such as electronics, books, and home goods. For example, when customers visit the Amazon homepage or a product category, they can find the latest books, gadgets, or fashion items featured in a dedicated “New Releases” section.

Browse by Interest for the Best Gifts

The “Browse by Interest for the Best Gifts” strategy allows customers to shop for gift ideas based on specific interests, making it easier to find the perfect present for any occasion. By categorizing products into themes like “gifts for him,” “gifts for tech lovers,” or “personalized gifts,” this strategy helps customers quickly discover items that suit the recipient’s personality or hobbies, increasing the likelihood of a purchase.

Real-World Example: 

Etsy uses the “Browse by Interest” strategy to help shoppers find the best gifts based on specific interests. When browsing for gifts, Etsy offers curated categories like “Gifts for Her,” “Gifts for Baby,” or “Gifts for Music Lovers.” This feature allows customers to explore personalized or niche gifts that align with the recipient’s passions.

Personalized Product Bundle Recommendations

Personalized product bundle recommendations are an effective way to increase the average order value by offering customers a set of related products at a discounted price. These bundles are tailored to a customer’s preferences based on their browsing history, past purchases, or interests. By suggesting complementary products together, this strategy not only provides a convenient shopping experience but also entices customers with the value of purchasing multiple items at once.

Real-World Example: 

Amazon uses personalized bundle recommendations by suggesting relevant product bundles based on a customer’s browsing or purchasing history. For instance, if a customer is looking at a camera, Amazon might recommend a bundle that includes the camera along with accessories like a memory card, camera bag, and tripod, often at a special price. 

To Sum Up: How Product Recommendations Can Transform Your Store

Using product recommendation tactics is a powerful way to enhance the customer experience, drive sales, and increase the average order value. Whether you use product quizzes, “People Also Bought” sections, or personalized suggestions, these strategies help connect customers with the right products and ultimately improve conversion rates and customer satisfaction.

Want to implement these strategies in your Shopify store? As a Shopify expert we can help you optimize your store with practical product recommendations and upselling techniques. Get in touch with us today to boost your sales.

FAQs Product Recommendations Examples 

1. What is an example of product recommendations?
Amazon’s “Customers Who Bought This Also Bought” section suggests related products based on customer behavior.

2. How do I recommend a product to someone?
Recommend a product based on the person’s needs, preferences, or past purchases. Personalize the suggestion for relevance.

3. How to give the best review for a product?
Provide honest feedback, highlight key features, mention pros and cons, and share your personal experience.

4. What are some effective product recommendation strategies?
Use “Customers Also Bought”, “Similar Products”, and “Recently Viewed” suggestions to drive sales.

5. How can product recommendations increase sales?
They encourage upselling, cross-selling, and increase the average order value by suggesting complementary items.