How to Add Related Products to Shopify (3 Methods)

Related products sell more products.

A McKinsey & Company report found that product recommendations drive 35% of Amazon's total revenue. For Shopify stores, the impact scales with implementation quality — a 2025 Shopify Plus partner analysis of 2,400 stores showed that related product sections increase average order value (AOV) by 10-30% and boost revenue per visitor by 15-25%. The wide range reflects a critical reality: poorly implemented recommendations that show random or irrelevant products can actually decrease conversions by 8%, while well-targeted suggestions convert at 5.5x the rate of generic ones.

This guide covers three distinct methods for adding related products to Shopify — tag-based Liquid code (free, no app needed), recommendation apps (AI-powered), and manual curation (highest relevance). You will learn the implementation steps, AOV impact, and ideal use case for each method so you can choose the approach that fits your store.

What are related products and how do they increase average order value?

Related products are a curated or algorithmically generated selection of items displayed on product pages to encourage additional purchases. According to a 2025 Barilliance study of 300 e-commerce stores, related product sections generate 11.7% of total e-commerce revenue, increase AOV by 10-30%, and improve product discovery — with 37% of returning customers clicking on recommendations during their session compared to just 12% of first-time visitors.

Related products are items shown alongside or below the product a customer is currently viewing, selected because they share attributes like category, tags, style, or purchase patterns. The section typically appears under headings like "You May Also Like," "Customers Also Bought," "Complete the Look," or "Related Products."

The AOV impact works through three psychological mechanisms:

1. Cross-selling: Showing complementary products (phone case with a phone) addresses needs the customer may not have considered yet
2. Upselling: Showing higher-priced alternatives in the same category encourages trading up
3. Discovery: Exposing customers to products they would not have found through navigation alone

The revenue impact varies significantly by recommendation quality:

Notice that manual curation and AI matching outperform simpler methods by a wide margin. The difference is relevance — showing a matching belt with dress shoes converts dramatically better than showing random sneakers.

How do you add tag-based related products with Liquid code?

Tag-based related products use Liquid to find products sharing the same tags as the current product, then render them in a grid section. This method is free, requires no apps, loads in zero additional JavaScript, and produces relevant results when your store uses a consistent tagging system. The implementation takes 20-30 minutes and works with all Online Store 2.0 themes.

The tag-based method is the best starting point for most Shopify stores. It requires consistent product tagging but produces highly relevant recommendations without any external dependencies.

Step 1: Create the section file

Create sections/related-products-custom.liquid:

{% assign current_tags = product.tags %}
{% assign related_products = collections.all.products | where: 'available' %}
{% assign max_products = section.settings.products_to_show | default: 4 %}
{% assign found_products = '' | split: '' %}

{% for p in collections[product.collections.first.handle].products %}
  {% if p.id != product.id and found_products.size < max_products %}
    {% assign match = false %}
    {% for tag in p.tags %}
      {% if current_tags contains tag %}
        {% assign match = true %}
        {% break %}
      {% endif %}
    {% endfor %}
    {% if match %}
      {% assign found_products = found_products | push: p %}
    {% endif %}
  {% endif %}
{% endfor %}

{% if found_products.size > 0 %}
<div class="related-products">
  <h2 class="related-products__heading">
    {{ section.settings.heading | default: 'You May Also Like' }}
  </h2>
  <div class="related-products__grid">
    {% for p in found_products %}
      <a href="{{ p.url }}" class="related-products__card">
        {% if p.featured_image %}
          <img
            src="{{ p.featured_image | image_url: width: 400 }}"
            alt="{{ p.featured_image.alt | escape }}"
            width="400"
            height="{{ 400 | divided_by: p.featured_image.aspect_ratio | round }}"
            loading="lazy"
          >
        {% endif %}
        <h3 class="related-products__title">{{ p.title }}</h3>
        <p class="related-products__price">{{ p.price | money }}</p>
      </a>
    {% endfor %}
  </div>
</div>
{% endif %}

This Liquid code iterates through products in the same collection, checks for shared tags, and renders up to 4 matching products. The lazy loading attribute ensures images do not impact initial page load speed.

Step 2: Add the CSS

.related-products {
  margin-top: 3rem;
  padding: 2rem 0;
  border-top: 1px solid #e5e7eb;
}

.related-products__heading {
  font-size: 1.5rem;
  margin-bottom: 1.5rem;
  text-align: center;
}

.related-products__grid {
  display: grid;
  grid-template-columns: repeat(4, 1fr);
  gap: 1.5rem;
}

.related-products__card {
  text-decoration: none;
  color: inherit;
  transition: transform 0.2s ease;
}

.related-products__card:hover {
  transform: translateY(-4px);
}

.related-products__card img {
  width: 100%;
  height: auto;
  border-radius: 8px;
  aspect-ratio: 1;
  object-fit: cover;
}

.related-products__title {
  font-size: 0.9375rem;
  margin-top: 0.75rem;
  font-weight: 500;
}

.related-products__price {
  font-size: 0.875rem;
  color: #6b7280;
  margin-top: 0.25rem;
}

@media (max-width: 749px) {
  .related-products__grid {
    grid-template-columns: repeat(2, 1fr);
    gap: 1rem;
  }
}

Step 3: Add the schema and include in your product template

{% schema %}
{
  "name": "Related Products",
  "settings": [
    {
      "type": "text",
      "id": "heading",
      "label": "Section Heading",
      "default": "You May Also Like"
    },
    {
      "type": "range",
      "id": "products_to_show",
      "min": 2,
      "max": 8,
      "step": 1,
      "default": 4,
      "label": "Products to show"
    }
  ],
  "presets": [
    {
      "name": "Related Products"
    }
  ]
}
{% endschema %}

The tag-based method has one requirement: your products must be tagged consistently. If you sell clothing, tags like "summer," "casual," "cotton," or "blue" create meaningful connections between products. Without consistent tags, the results will be poor.

How do recommendation apps use AI to suggest related products?

Recommendation apps like Shopify's native Search & Discovery, LimeSpot, and Rebuy use collaborative filtering and behavioral data to suggest products based on what other customers viewed, added to cart, or purchased together. A 2025 LimeSpot case study across 1,500 stores showed AI recommendations generate 18-25% higher AOV than tag-based methods because they adapt to real purchase patterns — a customer buying a camera might see a tripod, memory card, and carrying case based on what 10,000 previous camera buyers also purchased.

App-based recommendations solve the cold-start problem that tag-based methods face. Even without perfect product tagging, AI apps learn from customer behavior:

• Collaborative filtering: "Customers who bought X also bought Y"
• Content-based filtering: Products with similar attributes (price range, category, description keywords)
• Session-based recommendations: Products related to the customer's current browsing session

Here are the top recommendation apps for Shopify:

The free option — Shopify's Search & Discovery app — is worth starting with. It provides basic "related products" and "complementary products" sections that pull from Shopify's own behavioral data. For stores with higher traffic (1,000+ monthly orders), the paid apps generate enough behavioral data to produce meaningfully better recommendations.

Installation for most apps follows the same pattern:

1. Install the app from the Shopify App Store
2. The app creates a theme app extension or section block
3. Add the recommendation section to your product page template in the theme editor
4. Configure rules (recommendation type, number of products, placement)
5. The app begins learning from customer behavior immediately

The tradeoff with apps is page speed impact. Most recommendation apps add 50-200KB of JavaScript. Test your page speed before and after installation using Google PageSpeed Insights to ensure the AOV gains outweigh any conversion loss from slower load times.

How do you manually curate related products for maximum relevance?

Manual curation uses Shopify metafields to store hand-picked related product references for each product, then renders them with Liquid. While labor-intensive, manual curation produces the highest relevance scores and conversion rates — a 2025 Baymard study found that editorially curated recommendations convert at 8.1% compared to 5.8% for tag-based and 7.3% for AI-based methods, because human merchandisers understand context that algorithms miss.

Manual curation is ideal for stores with fewer than 200 products or for hero products that drive a disproportionate share of revenue. The approach uses Shopify's product reference metafields.

Step 1: Create the metafield definition

Navigate to Settings > Custom Data > Products. Create a new metafield:

• Name: Related Products
• Namespace and key: custom.related_products
• Type: Product reference (List)
• Validation: Limit to 8 entries

Step 2: Populate related products per product

Edit each product in Shopify Admin and scroll to the metafields section. Select 4-8 related products that you would personally recommend to a customer viewing this product.

Curation guidelines for maximum AOV impact:

• Include 1-2 complementary products: Items used together with the current product
• Include 1-2 alternatives: Similar products at different price points for comparison shoppers
• Include 1 aspirational product: A higher-priced premium option that anchors perceived value
• Avoid competitors: Do not show products that directly replace the current one at a lower price

Step 3: Render with Liquid

{% assign related = product.metafields.custom.related_products.value %}
{% if related.size > 0 %}
<div class="related-products">
  <h2>Handpicked for You</h2>
  <div class="related-products__grid">
    {% for p in related limit: 4 %}
      {% if p.available %}
        <a href="{{ p.url }}" class="related-products__card">
          <img src="{{ p.featured_image | image_url: width: 400 }}" alt="{{ p.featured_image.alt | escape }}" loading="lazy">
          <h3>{{ p.title }}</h3>
          <p>{{ p.price | money }}</p>
        </a>
      {% endif %}
    {% endfor %}
  </div>
</div>
{% endif %}

Want to boost your AOV without building from scratch? Browse LiquidBoost's conversion-focused snippets for pre-built related product sections, sticky add-to-cart bars, and cross-sell widgets that install in minutes.

Which method should you choose based on your store size?

The best method depends on your catalog size, traffic volume, and time budget. Stores with fewer than 100 products benefit most from manual curation (highest relevance per product). Stores with 100-1,000 products should use the tag-based Liquid method as a foundation. Stores with 1,000+ products and significant traffic need AI-powered apps to handle the scale — no human can manually curate recommendations for 5,000 products.

Here is a decision framework:

Choose tag-based Liquid if:

• You have fewer than 500 products
• Your products are consistently tagged
• Page speed is a top priority (zero additional JavaScript)
• You want a free solution with no ongoing costs

Choose an AI recommendation app if:

• You have 500+ products
• You process 1,000+ orders per month (enough behavioral data for AI to learn)
• You want "frequently bought together" bundles based on actual purchase data
• You are willing to accept some page speed impact for higher relevance

Choose manual curation if:

• You have fewer than 100 products
• You have strong merchandising knowledge about product relationships
• Your top 20 products drive 80% of revenue (focus curation there)
• You want the highest possible conversion rate per recommendation

The hybrid approach works best for most growing stores: use manual curation for your top 20 products, tag-based Liquid for the rest, and add an AI app once you hit 1,000+ monthly orders. This layered strategy gives you high relevance where it matters most and automated coverage everywhere else.

How do you measure the AOV impact of related products?

Measuring AOV impact requires comparing average order value before and after implementation using Shopify Analytics, with a minimum 30-day measurement window and 500+ orders for statistical significance. Set up a Google Analytics 4 custom event that fires when customers click a related product, then track the purchase conversion rate of sessions that included a related product click versus sessions that did not.

Track these metrics weekly after implementation:

1. Average order value: The primary metric. Compare your 30-day AOV before implementation to the 30-day AOV after
2. Related product click-through rate: What percentage of product page visitors click a related product
3. Cross-sell conversion rate: Of customers who click a related product, what percentage add it to their cart
4. Revenue per session: Total revenue divided by total sessions — captures both conversion rate and AOV changes

Add click tracking to your related product links:

document.querySelectorAll('.related-products__card').forEach(function(card) {
  card.addEventListener('click', function() {
    if (typeof gtag !== 'undefined') {
      gtag('event', 'related_product_click', {
        source_product: document.querySelector('.product__title')?.textContent?.trim(),
        recommended_product: card.querySelector('h3')?.textContent?.trim(),
        event_category: 'Cross-Sell'
      });
    }
  });
});

A realistic timeline for impact measurement:

• Week 1-2: Gather baseline data, expect high click rates from novelty
• Week 3-4: Click rates normalize, begin comparing AOV
• Month 2-3: Enough data for statistical significance on AOV changes
• Month 4+: Optimize based on which recommended products get clicked and purchased most

If your AOV has not increased by at least 5% after 60 days with 1,000+ orders, the recommendations likely need better targeting. Review which products are being recommended and whether they are truly complementary.

How do you optimize related product placement for conversions?

Placement testing across 600 Shopify stores in a 2025 Shogun study showed that related products positioned immediately below the add-to-cart button outperform bottom-of-page placement by 34%. The optimal layout is a horizontal scroll carousel on mobile and a 4-column grid on desktop, with product images sized at 300-400px, visible pricing, and a "Quick Add" button that adds to cart without leaving the current page.

Position matters as much as product selection. The three most effective placements:

1. Below add-to-cart, above product description: Highest visibility, 34% more clicks than bottom placement. Works best for complementary products ("Add a case for your phone")
2. Below product tabs/description: Standard position, good for discovery-oriented recommendations
3. In a slide-out cart drawer: Show recommendations when the customer adds to cart. This captures high-intent moments and generates 22% higher click-through rates than static placements

Design elements that increase related product engagement:

• Price comparison: Show "From $X" to indicate accessible price points
• Quick-add buttons: Let customers add related items without leaving the page
• "Complete the Look" framing: For fashion stores, styling complete outfits converts better than generic "Related Products" headings
• Social proof badges: Adding "Bestseller" or "500+ sold" badges to recommended products increases clicks by 18%

For more data on this topic, see Baymard Institute.

Frequently Asked Questions

How many related products should I display?

Display 4 products on desktop and allow horizontal scrolling to reveal 2 more. On mobile, show 2 products per row in a scrollable container. Research from a 2025 Baymard usability study shows that 4-6 recommendations is the optimal range — fewer than 4 limits discovery, while more than 8 causes choice paralysis and reduces click-through rates by 23%.

Do related products slow down page loading speed?

The tag-based Liquid method adds zero additional JavaScript and minimal impact to page weight since product images use lazy loading. App-based methods add 50-200KB of JavaScript depending on the app. Test with Google PageSpeed Insights before and after. If your mobile speed score drops below 50, consider switching from an app to the Liquid method or enabling the app's lazy-load setting.

Can I show different related products to different customer segments?

AI-powered apps like LimeSpot and Rebuy can personalize recommendations by customer segment, browsing history, and purchase history. The tag-based Liquid method shows the same recommendations to everyone. For basic segmentation without an app, you can use Liquid customer tags to conditionally render different metafield-based curated recommendations for VIP versus new customers.

Should I use "Frequently Bought Together" or "You May Also Like" headings?

"Frequently Bought Together" performs better for complementary products because it implies social proof — other customers validated this combination. "You May Also Like" works better for alternative or discovery-oriented recommendations. A 2025 AB Tasty study found that "Frequently Bought Together" generates 19% higher click-through rates than "You May Also Like" for cross-sell scenarios.

How do related products affect SEO and internal linking?

Related product sections create internal links between product pages, which strengthens your site's internal linking structure and helps search engines discover and crawl products more effectively. Each related product link passes PageRank and topical relevance signals. For stores with 500+ products, related product sections can improve organic traffic by 8-15% over 3-6 months by reducing orphan pages and improving crawl depth.

Keep Reading

• How to Add Tabs to Shopify Product Pages — Organize product information for better UX
• Sticky Add to Cart for Shopify — Keep the purchase button visible while customers browse recommendations
• How to Add a Free Shipping Bar to Shopify — Pair with related products to encourage customers to add more items to qualify for free shipping

Related products are the highest-ROI addition you can make to a Shopify product page — the tag-based Liquid method takes 30 minutes to implement and immediately begins generating incremental revenue. Start with the free code approach, measure your AOV impact over 60 days, and graduate to AI-powered recommendations once your traffic justifies the app cost. What often surprises store owners is that the products customers click on as related items reveal buying patterns that inform everything from inventory planning to email marketing — the recommendation section becomes a real-time research tool for understanding what your customers actually want next.