8 Product Recommendation Strategy Tips for eCommerce

Shoppers today expect more than just a list of products—they crave personalization that makes their online experience feel unique.

A solid product recommendation strategy helps you do exactly that by offering shoppers suggestions that feel tailored just for them.

Advanced product recommendation systems help create these moments by displaying personalized suggestions like similar products on product pages or complementary items at checkout.

Automated recommendations driven by AI increase conversions and order value, keeping customers engaged.

In this guide, we’ll cover 8 product recommendation best practices, explore how to tailor product suggestions for maximum impact and share strategic recommendations examples that drive real eCommerce results.

8 Product Recommendation Best Practices

1. Set Clear Objectives for Your Product Recommendation Strategy

To make your product recommendation strategy work, you need to know what you’re aiming for. 

Having clear goals will guide your product recommendation system and ensure it delivers real results—whether that’s boosting sales or building customer loyalty.

• Minimize Cart Abandonment: Use your product recommendation technology to display relevant product suggestions that nudge customers toward finishing their purchase instead of leaving their cart behind.
• Boost Average Order Value (AOV): Suggest similar product recommendations or complementary items that encourage customers to add more to their cart and increase their total spend.
• Improve Customer Retention: Advanced eCommerce product recommendations can offer personalized product suggestions, which help keep customers engaged and coming back for future purchases.
• Enhance Conversions: Automated product recommendations powered by a smart product recommendation algorithm can boost sales by using cross-sell and upsell strategies that turn interest into action.

These product recommendation best practices ensure that your strategy is aligned with your business goals, helping you track progress and make adjustments as needed. 

Incorporating these strategic recommendations will help you get the most out of your product recommendation system and truly enjoy the benefits of product recommendations.

2. Map the Customer Journey to Optimize Recommendations

To get the most out of your product recommendation strategy, it’s important to understand how customers move through your site.

Knowing where they are in their journey helps you deliver product suggestions that feel relevant and helpful at every step.

• First-Time Visitors: For those new to your site, show best-selling or trending products to make it easier for them to start browsing. This is a simple way to introduce them to popular items and guide their experience.
• Returning Shoppers: Tap into historical data to suggest products based on what they’ve purchased or viewed before. Personalized recommendations make returning customers feel recognized and increase the chances they’ll make another purchase.
• At Checkout: Recommend frequently bought together products or complementary items. This strategy is a great way to boost the average order value and help customers discover items they might not have thought about.

Mapping these touchpoints allows you to use your product recommendation system more effectively, creating smarter recommendations that lead to more sales and improved customer experiences.

3. Build Personalization with First-Party Data

To make your product recommendation strategy more effective, tapping into first-party data is a must.

This information, collected directly from your customers, allows you to tailor product suggestions that genuinely match their preferences. 

• Contextual Data: Take into account a customer’s location, the time of day, or even the weather. Recommending sunscreen during a hot day or cozy sweaters in the winter makes your suggestions more relevant and timely.
• Past Interactions: Look at what customers have previously bought or browsed. Offering similar products or related items based on their shopping history keeps your recommendations personalized and helpful.
• Search Data: Use customer search behavior to your advantage. Search data shows exactly what a shopper is looking for, making it a powerful tool for suggesting products that meet their immediate needs. Combining eCommerce search engines with product recommendation systems can make your suggestions even more targeted and effective.
• Real-Time Behavior: Track what customers are doing in real time, like the products they click on or spend the most time viewing. Using this real-time data helps you recommend items that reflect their current interests.

Personalizing recommendations with first-party data ensures that your product recommendation system resonates with customers and helps you drive more conversions.

4. Implement Key Recommendation Strategies to Maximize Impact

A successful product recommendation strategy isn’t one-size-fits-all.

It’s about using a variety of approaches that fit different business goals and customer needs. These strategic recommendations examples can help you boost engagement and drive more sales.

• Best Sellers & Trending Products: Show off your most popular items to grab the attention of new visitors. This product recommendation technique is a great way to guide shoppers toward products with a track record of success.
• New Arrivals: Promote the newest additions to your catalog for customers who like to stay updated. Keeping them informed about fresh products encourages exploration and repeat visits.
• Complementary Products: Suggest products that pair well with what customers are already viewing or have in their cart. This advanced product recommendation helps increase average order value by offering relevant product suggestions that enhance their current selection.
• Frequently Bought Together: Show items that other customers tend to purchase alongside the current product. Using this strategy recommendation example drives upsells and cross-sells, making it easier for shoppers to add more to their cart.
• Tailored Suggestions: Tap into customer data and your product recommendation algorithm to offer highly personalized suggestions. Automated product recommendations based on their behavior make the shopping experience feel more personal, boosting retention and repeat purchases.
• Exclusive Deals and Discounts: Feature special offers or limited-time deals to create urgency. Highlighting discounts as part of your product recommendation system can motivate faster decisions and increase conversion rates.

Incorporating these product recommendations best practices, along with a product recommendation system powered by the right technology, ensures you’re delivering the most relevant product suggestions at every stage of the customer journey.

The benefits of product recommendations are clear: more engagement, higher sales, and a stronger connection with your shoppers.

5. Refine Your Recommendation Algorithms

Choosing the right product recommendation strategy is just the first step.

To really maximize its impact, you need to fine-tune the algorithm behind it. Adjusting how your recommendation system works ensures that every product suggestion is as relevant and personalized as possible.

• Name and Organize Your Strategies: Clearly name each strategy within your system so you can easily track and analyze their performance. Choosing the right strategy for the campaign—whether it’s showing best sellers, trending products, or tailored suggestions—ensures you’re meeting specific business goals.
• Use Filters for Precision: Filters are key to ensuring the right products get recommended:
  • Include Filters: You can spotlight specific product types—like high-value items—to drive larger sales.
  • Exclude Filters: Keep irrelevant products out of the mix by filtering out items like discounted stock, off-season goods, or products that aren’t relevant to the customer.
• Use IF/THEN Filters for More Contextual Suggestions: Filters play a big role in making your product suggestions as relevant as possible. Using IF/THEN contextual filters can help you adjust recommendations based on specific conditions, ensuring each suggestion matches the customer’s context:
  • IF a customer is viewing a high-value product, THEN show recommendations over a certain price point to encourage larger purchases.
  • IF a customer has been browsing summer wear, THEN exclude any winter stock to keep the recommendations seasonal and relevant.

• Customize Your Rules: For greater control, setting custom rules allows you to be specific about what customers see. For instance:
  • Match Product Attributes: Only recommend items that share key features—like color, brand, or style—with the product being viewed.
  • Keep It in the Category: Ensure that recommendations stick to the same product category to keep them relevant and aligned with what the customer is already browsing.
• Fallbacks for Fewer Results: Sometimes, a strategy won’t return enough products to fill a widget. In these cases, having a fallback plan—such as switching to best sellers or most-viewed items—ensures you’re still offering relevant suggestions. Fallbacks will follow any existing filters, so even backup options stay aligned with your brand’s goals.

Fine-tuning your product recommendation algorithm through these tweaks gives you more control and flexibility, ensuring your strategy is always focused on providing the best customer experience while aligning with your business objectives.

6. Use Different Recommendation Strategies for Each Page Type

To get the most out of your product recommendation strategy, it’s key to tailor your product suggestions to fit each page type on your site.

Different pages offer unique opportunities to engage customers with relevant, personalized recommendations that can boost sales and satisfaction.

• Homepage: New visitors are often unfamiliar with your store, so showcasing best sellers or trending products is a great way to grab their attention. For returning customers, automated product recommendations based on their previous browsing or purchases make the shopping experience feel more personal and tailored to their tastes.
• Category Pages: When customers are browsing category pages, advanced product recommendations like “Most Popular in Category” or “New Arrivals” help guide their decision-making. This strategy recommendation example can make it easier for them to discover products they might not have considered, leading to higher engagement and conversions.
• Product Detail Pages (PDPs): On PDPs, similar product recommendations work best. Suggesting items that complement or are frequently bought together with the product the customer is viewing can lead to cross-sells and higher order values.
• Cart Page: Before checkout, use product recommendations to show complementary or frequently bought together items. This strategy recommendation example is a simple way to increase average order value (AOV) without overwhelming the customer.
• Search Results Pages: When customers don’t find exactly what they’re looking for, your product recommendation system can offer relevant alternatives. By combining an eCommerce search engine with a product recommendation algorithm, you can suggest related or popular products, guiding customers toward items they might not have considered.

By tailoring your product recommendation system to different pages, you create a more engaging and relevant shopping experience.

These product recommendations best practices help maximize the benefits of product recommendations, ensuring they’re timely and useful at every stage of the customer journey.

7. Use Real-Time Pop-Ups to Influence Purchasing Decisions

Pop-ups are a great way to offer product suggestions at exactly the right moment.

These real-time nudges can catch customers’ attention and boost sales by recommending products when they’re most likely to take action.

• Exit-Intent Pop-Ups: When a customer is about to leave your site, an exit-intent pop-up can offer special deals or similar product recommendations to encourage them to stay and reconsider. Using advanced product recommendations, you can suggest alternatives or discounts that might convince them to finish their purchase.
• Cart-Based Pop-Ups: Once a customer adds something to their cart, cart-based pop-ups can offer complementary items or upgrades. This is a smart way to use your product recommendation system to increase the chances of an upsell, showing them additional products that pair well with their current selection.

Real-time pop-ups, combined with automated product recommendations, create personalized experiences and maximize your chances of driving conversions.

It’s an easy, effective way to leverage the benefits of product recommendations.

8. Continuously Test and Optimize Your Recommendation Strategies

A strong product recommendation strategy isn’t something you can set up once and forget.

To get the most out of your product recommendation system, you need to regularly test and optimize your approach. This ensures you’re always using the most effective strategies to drive engagement and sales.

• A/B Testing: Try out different types of product suggestions to see what works best. Whether it’s best-sellers, similar product recommendations, or personalized offers, A/B testing helps you figure out which product recommendations best practices lead to higher engagement and conversions.
• Performance Comparisons: Compare the results of different product recommendation setups. For example, see how well a “Best Sellers” widget performs against a “Recently Viewed” section. These insights allow you to adjust your strategy recommendation, helping you pinpoint which recommendations lead to better results.

Optimizing your product recommendation strategy over time helps you stay ahead, fine-tuning your system to deliver the most relevant suggestions based on real customer behavior.

Update Your Product Recommendation Strategy Today

A solid product recommendation strategy is essential for driving sales and building customer loyalty.

Doofinder’s new AI-powered product recommendation system takes things up a notch by using on-site search data to create more personalized and relevant product suggestions, and facilitating eCommerce product discovery.

With advanced product recommendations that make cross-selling easier, you can increase average order value (AOV), save time, and keep customers happy.

If you’re looking for a way to optimize your product recommendations best practices and deliver smarter, automated product recommendations, Doofinder’s new technology is exactly what you need.

From boosting cross-sells to offering strategic recommendations for every step of the customer journey, the benefits of product recommendations powered by AI are clear.

Want to see how it works? Try Doofinder’s AI recommendations for free and experience the power of smarter product suggestions today!