7 Types of Product Recommendations to Boost Your Sales

A recent McKinsey study found that 71% of consumers expect personalized interactions, and 76% become frustrated when brands fail to deliver them. This shows how critical product recommendation strategies are. Businesses that align with these customer expectations can gain loyalty and drive revenue.

In this blog, we will explore emerging trends in various types of product recommendations—from AI-powered personalization to influencer-driven suggestions—and offer actionable steps to help brands stay ahead.

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What Are Product Recommendations?

Whether it’s a “You may also like” section or a bundle recommendation before checkout, these tools act like a digital assistant that helps shoppers find what they need (and what they didn’t know they needed).

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Benefits of Product Recommendations

• Boosts sales with minimal effort: Once product recommendations are set up, they automatically adjust to user behavior in real time. There’s no need for constant manual updates, yet they continue to help convert visitors into customers.
• Increases average order value (AOV): Recommendations encourage customers to spend more per visit. Whether it’s through upselling or cross-selling, the result is a bigger basket at checkout.
• Improves customer experience: Personalized recommendations save customers time and help them find what they’re looking for faster. The result is a smoother, less frustrating shopping experience, especially in stores with large product catalogs.
• Encourages repeat purchases: Showing returning shoppers new items in their favorite categories or suggesting products that match past purchases makes them feel remembered. This builds familiarity and keeps them coming back.
• Supports merchandising strategy: You can promote overstocked products, seasonal lines, or high-margin items through your recommendation system, while still keeping the experience relevant and tailored to each user.

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How Product Recommendations Change Based on Business Goals

While the core function of product recommendations is to suggest relevant items, the way they’re used can shift depending on your specific goal. Here's how they work in different scenarios:

1. Customer acquisition: When someone lands on your site for the first time, the goal is to grab their attention fast. Showing trending products, bestsellers, or what’s popular right now gives new users an easy way in, without overwhelming them with too many options.
2. Customer retention: For returning customers, recommendations become more personal. Based on past purchases and interactions, these suggestions remind shoppers of what they liked before, or introduce them to new items in their favorite categories. This helps maintain engagement and encourages long-term loyalty.
3. Upselling: Upselling-focused recommendations aim to get the customer to consider a slightly higher-end or premium version of what they’re already interested in. Think upgraded models, bigger sizes, or better features. It’s a subtle nudge that can lead to higher- order values without feeling pushy.
4. Cross-selling: This approach suggests complementary items—products that make sense together. For example, someone buying a new printer might be shown ink cartridges or paper packs. These “complete the package” suggestions increase basket size and improve the overall customer experience.

» Understand the differences between upselling and cross-selling in eCommerce

7 Types of Product Recommendations to Boost Your Sales

Not all product recommendations serve the same purpose. Below are some of the most effective types of product recommendations, how they work, and how to use them well.



1. Personalized Recommendations

These are dynamic suggestions tailored to each shopper’s behavior—like browsing history, past purchases, or real-time clicks. They create a more intuitive, one-on-one experience that improves conversion by showing shoppers what they’re most likely to want next.

Who is it best for? Fashion, beauty, and electronics brands focused on customer retention, loyalty, and upselling.

Best practices for incorporating personalized recommendations

• Update suggestions in real time as customers explore the site, this keeps recommendations fresh and timely.
• Use conversational language like “You might like” or “Just for you” to make suggestions feel helpful instead of pushy.

Real world example: Steve Madden

After a customer browses black boots or wedge heels, Steve Madden surfaces similar products in a “Just For You” row right on the homepage. This ensures that the moment they return, they feel like the store remembers their style.



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2. Frequently Bought Together

These suggestions surface complementary products that are often purchased with the item currently viewed or added to the cart. This approach encourages bundling and increases average order value.

Who is it best for? Electronics, beauty, home goods, and fashion brands focused on cross-selling at checkout.

Best practices for incorporating frequently bought together suggestions

• Limit the number of recommendations to 2–3 key add-ons to keep the experience focused and low-friction.
• Use pricing or bundle messaging like “Add both for 10% off” to reinforce value and motivate action.

Real-world example: Ally Fashion

In the cart, Ally Fashion shows a “We Think You Would Love These, Too” section with 3-4 jewelry or clothing items that match what the customer already has. It also highlights a bundle discount if they add them all.



» Improve the quality of your personalized product recommendations with Fast Simon's smart collections

3. Trending & Best-Sellers

This type highlights popular, high-performing products across your site, leveraging social proof and urgency to guide buying decisions.

Who is it best for? Brands focused on customer acquisition in fast-moving industries like fashion, tech, and cosmetics.

Best practices for incorporating trending & best-sellers

• Combine global product popularity with individual browsing behavior for a more personalized experience.
• Use badges like “Bestseller” or “Hot Right Now” and display ratings to build trust.

Real-world example: Hillberg & Berk

Hillberg & Berk’s “H&B You” section shows trending products based on what the customer has interacted with. In this example, the customer sees one charm under the category, likely based on past views or popular items. Though the layout is simple, it highlights what’s currently popular or personally relevant.



» Check out the upcoming personalization technology trends

4. New Arrivals

New arrival sections highlight the newest items in your catalog and catch the attention of repeat visitors who want to discover products that fit their style or needs. These sections show products tailored to each customer’s preferences to keep shoppers engaged and encourage them to return regularly.

Who is it best for? Fashion, tech, and seasonal brands that rely on newness to drive repeat visits.

Best practices for incorporating new arrivals

• Segment by user behavior so customers see new products that match their past interests or categories.
• Add “New” or “Just In” tags and place these products near the top of category or home pages for better visibility.

Real-world example: Ally Fashion

Ally Fashion uses this strategy to showcase new collections like spring dresses or summer tops in a “New Season” section on the homepage. Returning customers immediately see relevant product recommendations that match their tastes.



» Check out these best practices for selling seasonal products

5. Discounted & Special Offers

This recommendation type highlights products with price drops, exclusive deals, or time-limited promotions to drive urgency and impulse buys.

Who is it best for? Any retail brand, especially fashion, beauty, and travel businesses.

Best practices for incorporating discounted & special offers

• Personalize the deals shown by connecting them to user behavior—for example, showing discounts on browsed items.
• Emphasize urgency with elements like countdown timers or labels such as “Ends Today” or “Last Chance.”

Real-world example: Francesca's

Francesca’s promotes a strong summer sale with bold messaging like “All Dresses $35” and “Buy One Get One Free” banners. These offers are placed front and center on the homepage, making them impossible to miss. This is a great way to grab attention and drive immediate interest, especially from value-driven shoppers.



» Read more: 4 Best practices for eCommerce homepage promotions

6. Alternative Suggestions

Alternative product recommendations help shoppers explore similar items when they’re unsure about their original choice. These suggestions offer comparisons based on attributes like price, style, or functionality.

Who is it best for? Fashion, furniture, home décor, and electronics brands aiming to keep undecided shoppers engaged.

Best practices for incorporating alternative suggestions

• Show items that share key attributes with the original product—like color, cut, price, or brand.
• Make sure alternatives are in stock and clearly presented to avoid dead ends in the shopping journey.

Real world example: Francesca's

Francesca’s uses Fast Simon’s machine learning AI to analyze key product attributes. Customers browsing a specific dress find similar styles in colors and cuts that match their preferences, making the shopping experience smooth and personal.



» Make sure you know how to optimize product recommendations for eCommerce merchandising

7. Social Proof-Driven Recommendations

This type combines product recommendations with customer reviews, ratings, or testimonials to build trust and credibility. It’s especially powerful when integrated into product carousels or homepage modules.

Who is it best for? Fashion, beauty, and tech brands where trust and peer validation drive purchases.

Best practices for incorporating social proof

• Let customers filter reviews based on style, size, or fit to make testimonials more relatable.
• Display reviews or star ratings directly inside recommendation blocks to give shoppers an extra reason to click.

Real-world example: Steve Madden

Steve Madden includes detailed customer reviews with star ratings, verified buyer tags, and even fit feedback like “true to size.” On the JYPSEY GOLD LEATHER product page, shoppers can scroll through quotes like “She’s that girl” and filter by experience or age group.



» Understand how to leverage customer reviews for eCommerce merchandising

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Emerging Trends in Product Recommendations

The field of product recommendations is evolving rapidly, shaped by new technology and changing shopper behavior.

To stay competitive, businesses must not only understand the latest trends but also adapt how they deliver different types of product recommendations. Here are five key shifts—and what you can do to keep up.

1. AI-Driven Hyper-Personalization

• Trend: AI can now predict what customers want with surprising accuracy. It draws from browsing habits, past purchases, and real-time behavior to tailor suggestions that feel custom-made.
• How to adapt: Use AI tools that analyze customer data in real time and deliver personalized suggestions without being intrusive. The goal is to make each shopper feel understood, not watched.

» Here are the benefits of personalized search

2. Voice Commerce & Conversational AI

• Trend: Shoppers increasingly use voice assistants to find products, especially during quick searches or multitasking moments. Voice-driven search is becoming a natural part of the customer journey.
• How to adapt: Optimize your product content for voice search. Use clear, conversational language in titles and descriptions. Make it easy for voice interfaces to recommend the right products by including natural phrases customers are likely to say.

» Here's everything you need to know about voice commerce

3. Social Commerce & Influencer-Driven Recommendations

• Trend: Influencer content now drives many purchase decisions, particularly in fashion, beauty, and lifestyle sectors. Customers trust real people over polished ads.
• How to adapt: Integrate influencer-driven content into your recommendation strategies. Feature curated picks from creators or show products used in popular social posts.

» Learn more: Best practices for influencer marketing

4. Sustainability & Ethical Shopping Preferences

• Trend: More customers care about how products are made, what they’re made of, and whether their purchases align with their values.
• How to adapt: Recommend products with verified sustainability attributes, like eco-friendly materials or ethical sourcing certifications.

5. Omnichannel Personalization

• Trend: Shoppers switch between mobile, desktop, social, and email without expecting any drop in relevance. They want the same personalized experience no matter where they shop.
• How to adapt: Sync your recommendation engine across every touchpoint. If a customer adds a product on mobile, they should see related suggestions on desktop or in their email.

» Make sure you understand the power of omnichannel marketing

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Stay Ahead With Fast Simon

The way you implement product recommendations can shape how customers engage with your store. From personalized suggestions to trending products and smart collections, every choice plays a role in building trust and driving sales. To do this well, you need more than just data—you need the right tools.

Fast Simon can help you build a product recommendation strategy powered by real-time site search and machine learning. Whether you're looking to increase conversions, improve loyalty, or simply show customers what matters to them, our AI solutions make it easier.

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