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Last updated Fri May 24 2024

What are Product Recommendations? Types & Strategies

Product recommendations enhance the shopping experience, so they lead to higher revenues and better customer loyalty.

I created this guide for those looking to get a quick overview of product recommendations, including their types, examples, and quick ways to implement them properly.

Some good news for you right away—you can add recommendations to your store in minutes and have them work on autopilot.

In this post:

Create personalized shopping experiences for your visitors with AI
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Looking for more tips to grow your ecommerce business? Check these guides from our blog:

What are product recommendations?

Product recommendations are product listings created automatically through pre-developed rules or real-time algorithms to suggest relevant items to website visitors, based on their browsing behavior, purchasing history, or popularity among others.

Product recommendations can appear in embed boxes, popups, onsite notifications, lightboxes, emails, and dynamic product visualizations. The most common places for product recommendations on websites are homepages, product pages, and shopping cart pages.

Types of product recommendations

Product recommendationMeaning
Recently viewed itemsRemind customers of items they have visited and possibly shown interest in
Customer favoritesHighlight products with the best ratings from other customers
“Complete your look”Suggest complementary products to complete an outfit
“You might also like”Recommend items based on similar qualities to current product
Recommended accessoriesSuggest some compatible or complementary accessories
Products in contextShow products in a relevant context to encourage purchase
Recommendations based on quiz answersProvide tailored recommendations based on customer preferences given in a quiz
Personalized bundle recommendationsRecommend extra items to encourage buying them in a bundle for a special price
Similar productsRecommend items similar to those currently being viewed
People also boughtSuggest products others often buy together
Recommendations based on product use casesSuggest products based on specific use cases or scenarios
Product suggestions on checkoutRecommend additional or complementary items at the checkout page
you might also like
See how businesses are using these types:

How are product recommendations created?

Product recommendation systems suggest items by analyzing site data, such as visitor activity, sales, and product features.

They are categorized into two types: traditional (rule-based) and AI-powered (using self-learning algorithms).

Traditional product recommendation systems use three techniques (collaborative filtering, content-based filtering, and hybrid) to generate suggestions based on rules developed from the known preferences of either an individual customer or a customer group.

AI product recommender systems analyze both historical and real-time customer data to generate highly personalized and contextual suggestions without manual input.

Product recommendationsTraditionalAI-powered
ApproachRule-basedAutonomous, self-learning
Adaptability to real-time changesStaticDynamic and adaptive
Scalability and personalizationScalability and personalization limited to predefined rulesScalable and highly personalized, based on individual customers
MaintenanceRequires manual updates and maintenance of rules and conditionsMakes automated updates and self-learning, limited input from humans
Best recommedation types to createPeople also bought, similar products, new arrivalsPersonalized bundles, recommendations based on use cases, “you might also like”
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Case study

Black Ember drives 4K shoppers from the homepage to newly launched products:

Find out more

Product recommendations: strategies

Use these ideas to increase your sales with product recommendations:

  • Show the list of viewed products with AI-powered conversion boosters

  • Highlight discounted items with popups

  • Use social proof to showcase your products in action

  • Combine best-selling items from multiple categories

  • Recommend items that complement the viewed product

1. Show the list of viewed products with AI-powered conversion boosters

Product recommendations based on browsing history are highly relevant as they let shoppers revisit viewed items, reducing "decision fatigue" that comes from being overwhelmed by too many choices.

You can make those items accessible from any page on your store in two clicks.

One way to use this tactic is AI Wishlist.

AI Wishlist uses browsing data and sales performance to not only display recently viewed items but also do so based on purchase intention analysis.

Example:

In Dusk, shoppers can return to the items they viewed from any page. Onsite notifications (that animated bell) let them know, so they just need to click on it to see the recommendations along with images:

ai wishlist on dusk

Here's a closer look at this message:

notification feed with recommended products

When shoppers click it, they'll see more info about the products, along with size selectors and "add to cart" buttons:

recommended product

AI Wishlist displays these messages on autopilot (there's an AI algorithm running and analyzing data at all times), so it doesn't require any input.

Besides, there's no coding involved, too.

If you'd like to try AI Wishlist on your Shopify store, join the free beta testing (currently in the final stages). This feature helps ecommerce stores increase sales by 5% on autopilot.

Get a free account to get started:

No cc needed, free beta testing. Learn more about AI Wishlist

danmodified

"The notification feed at OddBalls has been instrumental in helping us to gather data, assist conversion rates, promoting new launches and ultimately generating revenue since we launched it. It's a fantastic feature that has been in use for over a year... We highly recommend the use of the feed for all stores."

Dan Mitchell, Ecommerce Manager OddBalls

2. Highlight discounted items with popups

Homepages are the most traffic-heavy pages, so businesses often use various tactics to drive traffic from there to products. They are usually packed with content (announcements, videos, social proof, etc.), so it makes sense to use popups to share sales promos and keep them clean.

In this product recommendation tactic, we are encouraging visitors to check out discounted items for customers looking for the best deals.

Example:

Patagonia uses website popups to direct new visitors' attention to recommended items, with links to product categories to help customers easily find products:

patagonia discounted product recommendations

This message appeared on the homepage about three seconds after I landed there, meaning that most visitors will see it.

Considering that about one million visit Patagonia's website monthly, this popup can easily lead tens of thousands of shoppers to discounted items.

If you'd like to share similar product recommendations, get a popup software. Let me recommend Wisepops—it's rated 4.8 stars on Shopify and 4.9 on Capterra.

Grab a free account to get started:

Unlimited free trial, no cc needed. See how businesses use Wisepops popups

soi paris logo

"We use Wisepops as a real marketing tool, to collect opt-in the easiest way in compliance with our strong brand identity. They offer multiple ways to customize and display pop-ups at every step of our customer journey, due to their really good segmentation of visitors. It is very easy to connect with Shopify and Klaviyo as well."

Soi Paris, a Wisepops user

See how you can get leads and sales with targeted popups:

3. Use social proof to recommend products in action

Flying Tiger is using a special section with social media photos of its products taken by customers. It's a great tactic to recommend products naturally, while also showing them in action.

The section features clickable Instagram and TikTok posts, users who published them, and a link to more customer-generated content:

recommend products with social proof

When we click a post—

We see the content (in this case a TikTok video), with the featured product recommendations for easy access:

tiktok video with product recommendation example

And—

If we like what we see, we can click the images of products and check them out. Or, if we feel confident, we can add them to the cart in one click.

See how businesses increase average order values by suggestions related and complementary products in popups:

How to make upsell popups [+examples]

4. Combine best performers from multiple categories

This strategy will attract more of your store visitors to explore products across various categories. If you show a few best-selling items from multiple categories, you can highlight the diversity of the offers as well as improve product discovery.

Like here—

We get product picks from three categories ("Staff favorite," "New Arrivals," and "On Sale") and more are available by clicking on tabs:

product recommendations from each category

This product recommendation tactic is an efficient way to display more products, which could be quite useful for retailers with a wide range of offerings.

Take a look at how other businesses convert visitors with sales:

Sales promotion examples

5. Recommend items that complement the viewed product

Suggesting items that go well with the product being viewed is a way to help customers imagine having them. That results in a positive and easier shopping experience.

Let's see some examples:

BYLT shows these suggestions to complement a simple white t-shirt (the section located at the bottom of the product page):

complete the look product recommendations

Next—

Fashion Nova takes it one step further, by recommending "similar styles" and complementary items alongside the main product:

product recommendations from fashion nova

Ideas to improve the shopping experience in your store:

Ecommerce personalization tactics

How to get started with product recommendations

You can add product recommendations to your website in two ways: by using a third-party tool or by developing a recommender system in-house.

Option #1: Get a product recommendation tool

This is the best way for small and mid-sized businesses.

You can get an app developed specifically for your ecommerce platform (Shopify, BigCommerce, etc.) and add product recommendations to your site with almost no coding in a matter of hours.

Here are some great ones:

  • Wisepops. This app creates personalized shopping experiences with AI Wishlist. It uses browsing activity, visitor profiles, and sales data to predict purchase intentions, automatically showcasing products visitors are most likely to buy

  • Optimizely. An advanced suggestion system for generating web and email product recommendations, allowing you to personalize customer experiences both on your website and in their email inboxes.

  • Nosto. A platform for creating enterprise-grade personalization, which includes product recommendations based on AI analysis of historical and real-time customer data.

Option #2: Develop your own recommendation algorithm

This option is the best for large businesses and retailers.

Developing a recommendation system in-house may require more time and effort, but it gives you full control over the algorithm, data, and process.

Summary

Product recommendations are a powerful tool that can make all the difference in converting visitors into customers. Whether you choose to use a third-party tool or develop your own recommendation algorithm, incorporating product recommendations into your website is an effective way to drive traffic and boost sales.

Oleksii Kovalenko

Oleksii Kovalenko is a digital marketing expert and a writer with a degree in international marketing. He has seven years of experience helping ecommerce store owners promote their businesses by writing detailed, in-depth guides.

Education:

Master's in International Marketing, Academy of Municipal Administration

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