Recommend Recently Viewed Products on the Checkout Page

This guide shows you how to use WooCommerce Product Recommendations to add a Leave These Behind? block of product recommendations at the bottom of your store’s Checkout page. The recommendations will include recently viewed, in-stock products that customers didn’t add to their cart.

Plugins/Extensions Used

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• WooCommerce
• WooCommerce Product Recommendations
• Storefront

Configuration

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To create the Leave These Behind? block of recommendations:

Create a “Leave These Behind?” Engine

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1. Create an Engine
   • Go to WooCommerce > Recommendations > Engines and click Create new.
   • Under Title, enter “Leave These Behind?”.
   • Choose the Generic Engine Type.
2. Add Filters
   • Locate the Filters section in the Engine Configuration panel.
   • Add a Recently Viewed Filter.
   • Select in to recommend products that the customer has viewed recently.
   • Add a Stock Status Filter.
   • Select is in the first dropdown.
   • Select In stock in the second one.
3. Add Amplifiers
   • Go to the Amplifiers section.
   • Add a Conversion Rate Amplifier.
   • Select high to low in the dropdown to recommend products with higher ratings first.
   • Add a Popularity Amplifier.
   • In the first dropdown, select high to low.
   • In the second one, choose a time interval, for example last 30 days, to favor top-selling products ordered in this period.
   Use the +/- buttons to increase/decrease the relative weight of the two Amplifiers.
4. Save the Engine Click the Create button to save the Engine you just created.

Deploy the “Leave These Behind?” Engine

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1. 1. Deploy the Engine Click Deploy in the message that appears after saving the Engine. Alternatively:
      • Navigate to WooCommerce > Recommendations > Locations.
      • Search for and select the “Leave These Behind?” Engine.
      • Click the Deploy button.
   2. Configure Display Settings
      • In the Title field, enter “Leave These Behind?”. This will be displayed above the recommended products.
      • Select a number of Product columns and Product rows for the product recommendations. Use the default settings to display a single row of 4 products.
   3. Choose Location Select the Location where you’d like the recommendations to appear. To display the recommendations after the checkout form, choose Checkout > After Checkout Form.

1. Finalize the Deployment Click Deploy to deploy this Engine to the specified Location.

Result

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Making Changes

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To edit the configuration of the “Leave These Behind?” Engine:

1. Navigate to WooCommerce > Recommendations > Engines.
2. Locate and Edit the “Leave These Behind?” Engine.
3. Update the Engine to save your changes.

To edit the Display Settings, Location, or Visibility Conditions of your recommendations:

1. Navigate to WooCommerce > Recommendations > Locations.
2. Go to the Checkout section.
3. Click the After Checkout Form tab.
4. Expand the “Leave These Behind?” Engine deployment and make changes as needed.
5. Save your changes.

If you have only deployed a few Engines on your site, you may find it easier to locate and edit the “Leave These Behind?” Engine deployment by navigating to WooCommerce > Recommendations > Locations > Overview.

Tips

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Don’t Overdo It

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Adding many recommendations to the same page or Location may reduce their impact and harm your store’s conversion rate. For this reason, Product Recommendations allows you to limit the maximum number of recommendation blocks offered per Location. To control this, navigate to WooCommerce > Settings > Recommendations and adjust the Recommendation Blocks Limit option. As a rule of thumb, it’s best to keep this value low, between 1 and 3. Remember that the extension prioritizes Engine deployments according to their relative position in the WooCommerce > Recommendations > Locations > [Page] > [Location] list. Try to position your best-performing Engine deployments higher, especially if you have entered a low value in the Recommendation Blocks Limit option. The Reports built into the extension will help you identify and prioritize the Engine deployments that perform better than others in the same Location.

Questions & Support

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