Everything You Need to Know About Product Recommendations

Imagine this: It's a hot August weekend and you're looking for something to cool you down in your cozy apartment. You grab your laptop and start scrolling through an online store for anything to bring your body temperature back to reasonable levels! Just as you're about to give up, a small section catches your eye – "Recommended for You." There it is. The perfect portable size fan for your place.

This magic moment? It's not the stars aligning, it's the marvel of product recommendations. These tailor-made suggestions have the power to turn frustration into delight, indecision into a purchase, and hours of endless browsing into a few minutes of joyful discovery.

In our digital age, these unsung heroes of the personalized shopping experience are playing an increasingly pivotal role in our shopping habits. In fact, according to Accenture's recent study, 91% of consumers are likely to shop with brands that offer relevant recommendations and promotions, proving that product recommendations should be part of every e-commerce strategy.

So, how do they work? What types are there, and how can online retailers make the most of them? Let's journey together through the digital aisles of e-commerce and unravel the mysteries of product recommendations! 

What are product recommendations?

E-commerce product recommendations are targeted suggestions made to customers about products or services they might be interested in, based on their preferences, behaviors, historical interactions, and other relevant data. These recommendations can be as straightforward as showing each new visitor a list of popular items or as complex as using an algorithm that presents every shopper with a specific set of products.

Ideally, suggested items would be tailored for each shopper to help enhance the user experience, increase customer engagement and ultimately, drive more sales. The more personalized the recommendations, the better – personalized product recommendations can increase click-throughs by more than 100%, versus generic product recommendations.

How do you achieve this? You utilize the data collected from each shopper to recommend products that are most likely to interest them. This can be based on:

• The user’s browsing and/or purchasing history
• The customer’s location profile
• Product affinities based on the behaviors and likes of similar shopper profiles
  
  

What types of product recommendations are there?

Product recommendations enhance the customer experience by minimizing the time spent searching for products and maximizing the probability of finding relevant items they like. These suggestions can be categorized into several types and based on various factors. Some of the most common types include:

• Popular Products: Displays products that are trending or frequently bought by customers
• Customers Also Bought/Viewed: Shows products that other customers have purchased or viewed in conjunction with the currently viewed item
• Frequently Bought Together: Suggests complementary products that are typically purchased together with the product currently in view or in the user's cart
• Recently Viewed: Reminds users of products they have recently viewed to encourage them to revisit their choices
• New Arrivals: Introduces recently added products that match the user's preferences
• Cross-Sell: Recommends complementary products or accessories that go well with the items in the user's cart
• Upsell: Proposes higher-end or premium alternatives to the product the user is considering
• Urgency: Spotlights products with limited availability or time-sensitive deals
• Similar Products: Showcases items that are similar to the one the user is currently viewing or has purchased in the past
• Top-Rated or Highly Reviewed: Recommends products with the best ratings and reviews from other customers
• Seasonal: Recommends products based on seasonal trends, holidays, or special events
• Diversify: Offers suggestions to introduce users to new and diverse products
  
  

Personalized Product Recommendations

Personalized recommendations are tailored to each customer based on their digital behavior. By using this information, e-commerce businesses can suggest products that are the most likely to interest them. These recommendations can fit into a few different categories:

• Behavioral: Recommends products based on user behaviors such as click patterns, browsing history, and purchase history
• Demographic-Based: Suggests products based on user demographics like age, gender, location, etc.
• Location-Based: Features products based on the user's geographic location.
• Contextual: Considers factors such as time, location, and device type to make relevant suggestions.
• Implicit Feedback: Gathers user preferences from digital body language like mouse movements, dwell time, or scrolling behavior.
  
  

Why are product recommendations so valuable?

Product recommendations offer a wide range of benefits to both e-commerce businesses and their customers.

E-Commerce Business Advantages:

• Higher Conversion Rates: When visitors are presented with products that resonate with their interests and needs, they are more likely to take the desired action, such as making a purchase or signing up for a service.
• Improved Customer Trust and Brand Loyalty: Shoppers who feel that a business understands their preferences and needs are more likely to become loyal and repeat buyers.
• Increased Revenue: By suggesting relevant products, businesses can encourage customers to make additional purchases, boosting their average order value and overall sales.
• Reduced Cart Abandonment: Shoppers are less likely to ditch their carts and more likely to complete a purchase when they are guided toward products they are interested in.
• Effective Inventory Management: By promoting specific products through recommendations, businesses can manage inventory more efficiently, reducing the risk of overstocking or understocking.
• Competitive Advantage: A superior shopping experience can attract and retain customers, giving digital businesses a competitive edge.
• Data-Driven Marketing: The insights gained from analyzing customer behavior and preferences through product recommendations can inform targeted marketing campaigns, improving the effectiveness of promotional efforts.
  
  

Customer Advantages:

• Enhanced Customer Experience: By suggesting items that are more relevant and engaging to the individual user, businesses can help customers navigate their shopping journey better, while also feeling like their needs are being met.
• Convenience and Ease: Recommendations streamline the shopping process by presenting relevant options upfront, creating a more user-friendly and intuitive shopping environment.
• Reduced Decision Fatigue: Well-targeted recommendations simplify the decision-making process by presenting a curated selection of products, making it easier for customers to make choices.
• Deeper Personal Connection: When customers receive recommendations that match their tastes, they feel valued and understood by the brand, fostering a sense of connection and loyalty.
• Discovery of New Products: Customers can discover items they may not have considered otherwise, leading to serendipitous discoveries and broader product exploration.
• Mobile Shopping Optimization: On mobile devices with limited screen space, product recommendations help customers efficiently browse and find products, improving the mobile shopping experience.
• Overall Customer Satisfaction: Finding products that align with their preferences and needs enhances customer satisfaction and confidence in their purchasing decisions.
  
  

Where can product recommendations be used?

Now that you know all the kinds of product recommendations, it’s time to know the best spots to place them!

Homepage

The homepage is the primary entry point for the lion’s share of shoppers, so it’s important to tailor it for each visitor by showcasing personalized product recommendations based on their browsing and purchase history. This can ensure you’re captivating users' attention from the moment they land on your site.

Product Detail Pages

Recommendations with prompts like, “Similar Products”, "Customers Also Bought" or "You May Also Like" are great ways to encourage customers to discover additional items they might be interested in that relate to the item they’re currently viewing, and typically perform best after the current product has been added to the cart.

Category Pages

Shoppers don’t always know what they’re looking for. The product category page should anticipate their interests and needs by introducing product recommendations that eliminate the need for users to scroll through long lists.

Search Results

When customers search for a product, display results that include recommended products based on similar searches, preferences and behaviors. This can improve the search experience while also helping customers discover new items.

Checkout and Cart Pages

Checkout and cart pages offer an excellent opportunity for up-selling and cross-selling. Try recommending complementary products, popular items, or new arrivals.  You can even highlight products that the customer has brought previously — this works especially well for grocery stores or sites selling items that a customer might buy regularly, like makeup.

404 Page 

Nobody wants to land on a page and be told they took a wrong turn. To prevent this from being the end of your customer’s journey, add popular products, wishlist items, or similar products to the one that returned a 404 page to create opportunities and inspire your customers to continue shopping.

Pop-ups

Use dynamic pop-ups, sliders, or overlays to showcase relevant products based on the user's current browsing session or past sessions.

These pop-ups can appear as users navigate through the site, and when used appropriately, can turn hesitant customers into loyal brand advocates. According to Optimonk, the average pop-up has a conversion rate of 11.09%, but the best performing ones can convert over 42% of the time.

Email Campaigns

Sending targeted emails featuring recommended products related to a customer's recent purchases, abandoned cart items, or wishlist products can re-engage customers and entice them to make a purchase. Have an e-newsletter? See if you can add personalized product recommendations to them as well.

Social Media 

Advertising on social media platforms like Tik Tok, Instagram, and Facebook can help you offer more e-commerce product recommendations to your users, which can significantly enhance the shopping experience and increase conversion rates.

How do AI and Machine Learning power product recommendations?

Machine learning and AI tools, like Granify, play a crucial role in generating product recommendations for e-commerce businesses by analyzing user behavior, preferences, and product data to provide personalized and relevant suggestions.

To add layers of personalization to a customer’s shopping experience, recommendation algorithms often take 3 approaches:

1. Collaborative filtering, which considers data from multiple shoppers and sources and cross-references their purchase histories to predict what a particular customer would like. These recommendations can be either user-based (suggesting products based on the preferences of similar users) or item-based (suggesting products similar to those the user has purchased or shown interest in).
2. Content-based filtering, which analyzes a shopper’s previous purchase preferences and history to create a preference profile.Products are then recommended based on the attributes, features, and characteristics of items the user has interacted with.
3. Hybrid filtering, which combines collaborative and content-based filtering systems by using data from similar users as well as a specific user’s past preferences to create the most accurate list of recommended products.
   
   

What are product recommendation best practices?

These tips will not only maximize the impact of every product recommendation widget you deploy, but also help you deliver the best experience possible to your customers.

Real-Time Data Collection and Integration

For product recommendations to work in your favor, you must make sure that the suggestions you offer are relevant and data-driven. Gather relevant and comprehensive data about your products, your customers, and their interactions, and always ensure recommendations are updated in real-time based on the user's current browsing or shopping session. This will enhance the relevance of the items suggested.

Placement and Design

The products recommended can vary, so it’s important to be able to customize and alter the layout and functionality of every widget. Look for a product recommendation engine that allows you to incorporate tests and personalization tactics. This can include positioning recommendations in different areas of the page and site for different audiences, or allowing you to alter the layout or recommendations according to each visitor’s preferences.

Always Above the Fold

The position of product recommendations influences how effective they are. Make it easy for shoppers to spot your suggestions easily by placing them above the ‘fold’ – showcasing them when a user first lands on a page, rather than making them scroll.

Clear and Concise Wording

Now is not the time to get whimsical with words. Keep it simple by using direct language that’s easy for customers to understand and act upon, and draws attention to your recommended products.

High-Quality Product Images

Great product pics are a must-have for product recommendations because they increase the likelihood of a customer making a purchase. Always use high-resolution images that load quickly on both your website and mobile devices.

A Sense of Urgency 

The entire essence of product recommendation is getting users to make purchases right away and not saving them for later. Creating a sense of urgency allows you to take maximum advantage of people’s FOMO (that’s fear of missing out, if you’re not hip to the slang).

Front and Center Discounts

Most consumers love (and seek) good deals, so highlight any offers to give them a bigger reason to buy.  This strategy works particularly well for impulse purchases.

Social Proof

From user-generated reviews and testimonials, to badges that build trust, showcasing social proof is a great way to prove value to your customers. In fact, 46% of consumers trust online reviews as much as they trust recommendations that come from friends and family. (Source: BrightLocal)

Mobile Optimization

Ensure that your product recommendations are easily scrollable on mobile devices, as a significant portion (over 55%, to be exact) of e-commerce traffic comes from smartphones and tablets.

Testing and Optimization

A/B testing different recommendation strategies will come in handy as you’re looking to understand which recommendation strategy works best. Continuously test and optimize your recommendation algorithms, and experiment with different recommendation strategies and placements on the website, to find the most effective approach.

Closing Remarks

In the grand bazaar of online commerce, the significance of e-commerce product recommendations cannot be overstated. These intelligent companions on our digital shopping journeys have proven their worth in enhancing user experiences, boosting sales, and forging lasting connections between customers and brands.

By understanding their value and using the best practices we’ve suggested, you’ll be able to help your customers find exactly the right product, while also increasing your conversion rate and average order value. With e-commerce product recommendations in your toolbelt, the path to discovery and satisfaction awaits.

Tailor Your Product Suggestions 

Granify and personalized product recommendations go together like peanut butter and jelly, wine and cheese (or wine and online shopping), and most importantly, delighted customers and higher conversions. Talk to our team today to find out how our advanced AI-powered platform takes product recommendations to the next level to increase conversions–and revenue!–for our partners.