How to Set Up Product Recommendations on Shopify

If you’re running a Shopify store, adding product recommendations is one of the easiest ways to boost sales and help customers find what they’re looking for. Whether it’s “Frequently Bought Together” suggestions or personalized picks, these little nudges can increase your average order value and keep shoppers browsing for longer. In this guide, we’ll break down how to set up product recommendations on Shopify, from choosing the right tools to tracking results, so you can get more from every visit.

• Benefits: Recommendations like "Frequently Bought Together" and "Personalized Suggestions" can increase average order value and conversion rates.
• Steps:
  1. Analyze store data using tools like Shopify Analytics.
  2. Choose products to recommend based on performance and inventory.
  3. Install a recommendation app like LimeSpot or use Shopify's built-in features.
  4. Configure settings, customize designs, and test placements.
• Optimization: Track metrics like click-through rates and average order value. Use A/B testing to refine strategies.
• Advanced Options: For tailored solutions, use Shopify's Liquid coding or hire experts for custom implementations.

For clients like Made4Fighters, personalized product suggestions — such as “You May Also Like” recommendations shown at checkout — help guide customers toward complementary items, boosting average order values and encouraging more complete purchases.

They also feature product recommendations right below product pages, shown in the “People Also Bought” section. These suggestions are carefully placed to catch attention as customers scroll, working seamlessly on both mobile and desktop. This makes it easy for shoppers to spot matching products without hunting around — helping them add a little more to their cart and boosting order values along the way.

Setting Up Your Store for Recommendations

To make the most of product recommendations, start by analyzing your store's data and identifying key products that can drive sales. A solid understanding of your metrics will help you uncover customer preferences and trends.

Review Your Store Data

Dive into tools like Shopify Analytics and Google Analytics to assess your store’s performance. Pay attention to:

• Sales Data: Look at your top-selling items, average order value (AOV), and conversion rates.
• Customer Behavior: Analyze metrics like page views, time spent on specific pages, and click-through rates.
• Search Trends: Keep an eye on the most-searched terms in your store.
• Cart Activity: Study cart abandonment rates and which products are often purchased together.

Choose Products to Recommend

Use the data you’ve gathered to select products that align with customer interests. Prioritize items that are performing well and pair naturally with others.

Key considerations include:

• Inventory Levels: Ensure you have enough stock to meet potential demand.
• Product Performance: Highlight items with high conversion rates, strong customer reviews, and good profit margins.
• Natural Pairings: Recommend complementary items, like phone cases with phones or accessories with outfits.

Keep your product listings detailed and up to date to improve the quality of recommendations and provide a better shopping experience.

Adding Product Recommendations on Shopify

Finding the right recommendation app means understanding what your store needs and comparing available options. Apps like LimeSpot Personalizer (rated 4.9/5 stars from over 1,300 reviews) are popular for their AI-driven personalized recommendations.

When evaluating apps, prioritize these features:

• AI-based algorithms that analyze customer behavior
• Customization options to match your store's design
• Easy integration with your current theme
• Low impact on page loading speed
• Analytics tools to track recommendation performance

Set Up and Configure Your App

1. Install the app from the Shopify App Store and approve permissions.
2. Adjust the recommendation settings to fit your store's needs.
3. Decide where recommendations should appear on key pages.
4. Customize the design to align with your brand's look and feel.
5. Define rules and filters for the types of products to recommend.

Tip: Start small by adding recommendations to product pages first. Use performance data to decide when and where to expand.

Use Custom Code for Advanced Solutions

For more tailored recommendation logic, Shopify's Liquid coding language provides flexibility. Here's a simple example using the Product Recommendations API:

{% for product in recommendations.products %}
  <div class="product-recommendation">
    <img src="{{ product.featured_image | img_url: 'medium' }}">
    <h3>{{ product.title }}</h3>
    <p>{{ product.price | money }}</p>
  </div>
{% endfor %}

This code displays recommended products dynamically. Always test these changes to ensure they work smoothly with your store's design. For more complex setups, you might want to collaborate with developers experienced in Shopify, like UltraLabs.

When creating custom solutions, pay attention to:

• Page speed to ensure recommendations don't slow down your site
• Mobile-friendly designs for all widgets
• A/B testing to find the best placement and styles
• Error handling for cases where recommendations might not load

After setting up, monitor key metrics to measure the success of your recommendations and make improvements as needed.

Measure and Improve Results

Track your product recommendations to help boost ecommerce revenues by as much as 35%.

Check Key Metrics

Start by keeping an eye on these important metrics:

To track clicks on product recommendations, use this code in your product template:

$('.recommendation-link').on('click', function() {
  ga('send', 'event', 'Product Recommendation', 'Click', $(this).data('product-id'));
});

Test Different Approaches

Once you're tracking these metrics, test and refine your recommendations to improve their effectiveness.

Here are a few ways to experiment:

• Compare different recommendation types, like "Frequently Bought Together" versus "Customers Also Viewed"
• Test placement on various pages, such as product pages, the cart page, or the homepage
• Try different display formats, such as grids versus carousels
• Experiment with showing 3 items versus 5 items

Run these tests for about 4 weeks, ensuring traffic is evenly split between variations. Use tools like Shopify's analytics and your recommendation app's dashboard to assess the impact of each change.

For more advanced improvements, consider AI-powered tools like LimeSpot. These tools can automatically adjust recommendations based on real-time data and have been shown to boost conversion rates by up to 40% ^[1]. Use this data to fine-tune your strategy and keep your recommendations performing at their best.

Signs You Need Expert Help

Not sure if you need professional support? Here are some common challenges that signal it might be time to call in the pros:

• Managing large catalogs with 1,000+ SKUs or navigating multi-channel integrations
• Heavy site traffic but low conversion rates
• Product suggestions that feel off or irrelevant
• Difficulty implementing advanced features like real-time personalization or predictive recommendations

If your data shows ongoing issues - like persistently low conversions - expert help can turn things around. UltraLabs can implement solutions like:

• Predictive recommendations based on customer browsing habits
• Dynamic pricing that adjusts with inventory levels
• Cross-category suggestions to introduce shoppers to new products
• Time-sensitive recommendations timed to match shopping patterns

The process typically takes 4-6 weeks, with regular audits to keep your system performing at its best.

Conclusion

Setting up product recommendations on Shopify doesn’t have to be complicated. Start with solid data, choose tools that fit your store, and keep an eye on how things perform. Test, tweak, and don’t be afraid to get help if things feel too technical. In the end, smart recommendations can make shopping easier for your customers and bring in more sales for you — a win on both sides.

Maintenance Tips

To keep your recommendations effective, make updates a regular habit. Refresh your product data, listen to customer feedback, and track key metrics like click-through and conversion rates to ensure relevance.

Here are some best practices:

• Quarterly Updates: Adjust recommendation rules to match seasonal trends.
• Experiment Regularly: Test different widget placements every 2-3 months to see what works best.
• Algorithm Tweaks: Refine your algorithms based on performance data for better results.
• Email Integration: Sync product recommendations with email campaigns for a unified strategy.