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We are excited to announce that Algolia Recommend is now available for our Adobe Commerce customers. This has been a highly requested feature by retailers, many of whom have been already using Algolia to power search on Adobe Commerce, and are ready to take discovery to the next level.

I have good search – Why do I also need recommendations?

Recommendations change the typical dynamic of being online: rather than needing to search to find content, recommendations find the content for you. Netflix has said that 80% of people watching on Netflix came from their recommendation algorithm. Moreover, 35% of Amazon revenue comes from product recommendations. Once you have search optimized on your ecommerce site, having relevant recommendations is typically the next area of investment. Having the right recommendations underneath a product details page, on the shopping cart, or as a suggestion upon a “no results” search query can be a game changer.

Co-op, a UK-based grocery store, added recommendations for whenever a user searched for an item out of inventory. They found that while it was a frustrating experience to have your desired product out of stock, they could reduce the friction, improve the customer experience, and get better results by offering related products that the user likely could see as a replacement.

Co-op UK grocery store's website - screenshot of a search with no results and recommended products

After implementing Algolia Recommend, Co-op saw: 

  • 6% larger basket sizes
  • 45% increase in items added to basket
  • 39% increase in conversions

What sets Algolia Recommend apart?

Algolia is known for the flexibility with which we offer AI-based solutions. You can always customize your results, place them anywhere that you would like (whether it be a kiosk, email, or anywhere on your site), and you have transparency into how everything is performing through simulations and scoring to understand why things are being recommended, before going live.

Algolia allows users to blend machine- and human-learning through “Rules” in order to achieve the best results (currently in beta). For example, you may want to display related items on a product listing page. Not only does Algolia use AI to surface similar products likely to be chosen by your customers, we allow you to customize it even further. Perhaps you want all of the recommended items to be the same color as the main product displayed, or maybe you want to pin a promoted item in the first position, or you might want to filter all products that have less than 10 pieces left in inventory. All of this (and much more) is possible and easy to configure for a non-technical administrator using Algolia Recommend.

How do I get started?

1. Bring in event data

After signing up for Algolia (get started for free right here), it is important to bring click and conversion events into your account to train your models. This is available out-of-the-box with the Magento integration. For more details, refer to the documentation. As you are getting started, you can use our content-based learning models, or upload past events via a .CSV file to accelerate the learning process.

2. Train your models

Through your Algolia dashboard, you can select the indices and train the models based on your click and conversion data. You can further customize the results with Rules. You can also use the Preview feature to simulate the results.

Algolia Dashboard Recommend models screenshot

3. Add Recommend modules to your PDP Pages

With a few clicks on the Magento Dashboard, you can add your “Related Products”, “Frequently Bought Together”, and “Trending” recommendations to your Product Detail Pages or Cart Page. These recommendations can be further customized by a developer, including being placed on other areas of your site.

magento recommend product settings page

Getting started with Algolia Recommend is simple, effective, and worthwhile. Thanks for reading and check out our documentation to learn more!


For more ideas on how to make the most of Algolia in your Adobe stack, check out the rest of our Integration Series, with articles on how to use Algolia with Adobe Experience Manager, Adobe Launch, and Adobe Analytics!

About the authors
Debanshi Bheda

Global Alliances Director - Algolia

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Rachel Trott

Engineering Lead, Magento

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