Relevant Cart Suggestions: A Step-by-Step Guide

This guide explains how to make product recommendations in your ecommerce cart more relevant to each shopper, which increases average order value and reduces cart abandonment. You’ll learn practical methods to personalize suggestions based on browsing behavior, purchase history, and cart contents. No coding is required, but basic familiarity with your ecommerce platform’s admin panel is helpful.

What You’ll Need

• Admin access to your ecommerce platform (Shopify, WooCommerce, BigCommerce, etc.)
• Product data: categories, tags, prices, and ideally past purchase data
• An analytics tool (Google Analytics, platform built-in) to see what customers view and buy
• A tool or app for recommendations (many platforms have built-in options; third-party apps can provide more advanced logic)

Step-by-Step

1. Collect and organize product data. Ensure every product has accurate categories, tags, and attributes (e.g., color, size, type). This is the foundation for any recommendation logic. If you have past orders, export them to understand which products are frequently bought together.
2. Analyze your current cart abandonment and upsell metrics. Look at your platform’s analytics or Google Analytics to see how often customers add items to cart and then leave. Also check the conversion rate of any existing recommendations. This gives you a baseline to measure improvement.
3. Choose a recommendation strategy. Pick one or more of these common approaches:
   • Frequently Bought Together: Use purchase history to find items often purchased in the same order (e.g., a camera and a memory card).
   • Complementary Products: Recommend items that logically go with what’s in the cart (e.g., a phone case for a phone). This can be based on categories or manually defined rules.
   • Customer-Specific (Personalized): Show suggestions based on the customer’s past browsing or purchase history. If they bought running shoes last time, suggest running socks now.
   • Popular in Category: Show bestsellers from the same category as the cart item. Good for new customers with no history.
4. Implement the chosen strategy. In your ecommerce platform, look for a “cart recommendations” or “related products” setting. If using a third-party app, install it and configure the logic. For example, in Shopify, you can use the “Shopify Search & Discovery” app or a third-party app like “Also Bought”. For WooCommerce, plugins like “Product Recommendations” or “Frequently Bought Together” are common.
5. Set the number of suggestions. Show 2 to 4 suggestions. Too many can overwhelm the customer and slow down the cart page. A/B test to see what works best for your audience.
6. Define the display rules. Decide when to show suggestions: always in the cart, only when the cart total is below a certain amount (e.g., to reach free shipping threshold), or only for specific products. For example, if you offer free shipping over $50, show suggestions that help the customer reach that threshold.
7. Add a clear call-to-action. Each suggestion should have a button like “Add to Cart” or “Add to Order” so the customer can add it without leaving the cart page. Make the button prominent but not distracting.
8. Test and optimize. Run A/B tests to compare different strategies, numbers of suggestions, and placements. Monitor metrics like add-to-cart rate from suggestions, average order value, and cart abandonment rate. Use the data to refine your approach.

Common Mistakes

• Showing irrelevant suggestions: Recommending a phone case when the cart has a laptop is not helpful. Always ensure suggestions are logically related to the cart contents.
• Ignoring customer history: If a customer already bought a product, don’t recommend it again. Use purchase history to exclude items they already own.
• Too many suggestions: Showing 10 products can cause choice paralysis and slow down the page, leading to higher abandonment.
• Not testing: Assuming one strategy works forever. Customer behavior changes, so you need to test and update regularly.
• Forgetting mobile: Ensure suggestions are easy to tap and don’t clutter the small screen.

Tips

• Use real-time behavior: If a customer has been browsing a specific category, show suggestions from that category even if it’s not directly related to the cart item.
• Leverage social proof: Add small labels like “Bestseller” or “Frequently bought together” to increase trust and click-through.
• Consider price range: Suggest items in a similar price range to the cart total. If they’re buying a budget item, don’t suggest a luxury alternative.
• Update recommendations regularly: Refresh your “frequently bought together” data monthly to reflect new products and changing trends.
• Use urgency sparingly: Phrases like “Only 3 left” can encourage action but overuse can feel manipulative.

Troubleshooting

• Suggestions not appearing: Check if the recommendation app is properly installed and enabled. Ensure your theme supports the app’s placement. Clear cache and test on a different browser.
• Suggestions are irrelevant: Review your product categories and tags. If they are too broad, the algorithm will match incorrectly. Refine your data and consider manual rules for key products.
• Low click-through on suggestions: Test different placements (above the cart total, below the items) and different text. Maybe the suggestions are not visible enough. Try adding a heading like “You may also need” to draw attention.
• Page speed issues: Recommendations can slow down the cart page. Use a lightweight app, limit the number of suggestions, and consider lazy-loading the suggestion section.
• Suggestions not personalized for returning customers: Ensure your platform is tracking customer login. If not, the system cannot use history. Encourage customers to log in.

Frequently Asked Questions

What is the best recommendation strategy?

There is no single best; it depends on your product range and customer base. For most stores, a combination of “Frequently Bought Together” and “Complementary Products” works well. Test to see what your customers respond to.

How many suggestions should I show?

Typically 2 to 4. This is enough to provide options without overwhelming the customer. A/B test to find the optimal number for your store.

Can I do this without an app?

Some platforms have built-in features (e.g., Shopify’s Search & Discovery). If not, you can manually add recommendations via code, but that requires developer skills. Apps are easier and often more powerful.

How often should I update my recommendation data?

At least once a month for frequently-bought-together data. If you have a large catalog or frequent new products, update more often to keep suggestions fresh.

Will recommendations work for new customers with no history?

Yes. For new customers, use popularity-based suggestions (bestsellers in the same category) or complementary products. Once they browse or buy, you can personalize.

Can I exclude certain products from being suggested?

Yes. Most apps allow you to set exclusion rules, such as excluding low-margin items or products that are out of stock. Check your app’s settings.

Related

• Creator Social Media Workflow: A Practical Guide
• Delete Postgres User? Safe Steps & What Happens
• Phone Call Background Samsung: Fixes & Causes