Product Recommendations from Adobe Sensei now integrated with Page Builder in Magento

Companies present on the Internet are constantly looking for solutions that will help them stand out above their competition and guarantee their customers the best possible experience in contact with their brand. Today, it is an issue that comes to the fore in particular, because sellers must adapt to the needs of recipients as much as possible, empathize with their situation and meet their expectations with the products offered and thanks to the friendly message of the entire brand. How does Magento Commerce help in achieving this goal?

 

What’s new in Magento

To help owners of online businesses, Magento offers a new solution in which Product Recommendations for Magento Commerce are integrated with the Magento content creation tool, the Website Builder. With such a solution, you can diversify your recommendations even more by extending the built-in Magento Admin environment to streamline your workflow. Moreover, it makes Magento merchants seamlessly drag and drop Adobe Sensei-based recommendation units anywhere in the content they previously create by themselves in Website Builder.

 

New opportunities offered by Magento and Sensei were made available to Magento Commerce users in April this year. These are the already mentioned product recommendations based on Adobe Sensei, artificial intelligence and machine learning technology. This feature allows store owners to implement automated and smart recommendations across all storefronts. This helps customers discover new products, appropriately matched to their preferences, which were discovered during their shopping journey through the store. All this takes place while increasing user engagement, increasing the conversion rate and, as a result, increasing the company’s revenues.

 

How does the new feature affect the functioning of Magento Commerce?

The Magento company, by making the new extension available in the Magento Marketplace, immediately recorded over 250 downloads. This means that a significant proportion of large and small companies use the potential of artificial intelligence to ensure effective growth. Such villages arise right away, because it’s no secret that different organizations are looking for newer and newer ways to drive growth while maintaining the same level of costs, and solutions based on artificial intelligence support both approaches. For this reason, the company has gone a step further since the implementation of the new recommendation feature. It focused on bridging the gap between intelligent merchandising and content management.

 

What are the most important benefits of Website Builder integration? 

The key benefits of Website Builder integration include:

 

  • The presence of the “drag and drop” function. Thanks to it, you can place product recommendations in any position between the editable content. All this is possible thanks to the Website Builder, which, moreover, is very simple and intuitive to use.
  • Ability to add a recommendation unit to many types of content, such as pages, blocks, dynamic blocks, and single fields. You will do it yourself, without the need to involve other specialists.
  • The ability to direct recommendations to specific customers by assigning dynamic blocks to various consumer segments. For example – you can use dynamic blocks to show your most loyal customer a highly personalized selection of products recommended to him. On the other hand, a different customer may receive a completely different set, because it will fit a different type of recommended products.
  • The presence of a page builder that will allow you to implement specific orders on a particular product page instead of all product pages.
  • Customize the recommendation unit in Website Builder to fit (be consistent with) your branding with colors, borders, headline style, and more.

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Andrzej Szylar

Andrzej Szylar

Chief Executive Officer

Dariusz Kobza

Dariusz Kobza

PR & Marketing Manager

Magdalena Paczynska

Magdalena Paczyńska

HR Business Partner