Introducing Experience-Driven Recommendations

Niklas Winkels
Niklas Winkels

For a long time, eCommerce has been on the hunt for the holy grail of personalization – a consistent, cross-channel experience that adapts to customer needs and goals in real-time.

In today’s personalization industry, everyone collects source data (where you came from – e.g. referral source: campaign, email), journey data and preferences (e.g. browse behavior) and who you are and what type of customer you are (e.g. logged in, past purchase data).

But to deliver relevant customer experiences through personalized recommendations across the entire customer journey, you need to deeply understand the products and services you’re recommending. 

To achieve this, Bloomreach additionally collects which facets/filters perform best for each query, which product attributes an individual and a segment cares most about and which products perform best for each query.

Personalization in commerce requires an understanding of your customer. Personalization that drives outcomes in commerce means understanding products as well as you understand people.

The good news for personalization is that these technologies have arrived.


Bloomreach is excited to announce Experience-Driven Recommendations. 🎉


With more than 6 major features, multiple feature enhancements and stability fixes, the release is a significant milestone for Bloomreach Recommendations. It includes the following features:

  • Experience-Driven Recommendations
  • Analytics for Recommendations 
  • Algorithm Improvement – Neural Embedding
  • UI Enhancements – Numeric Sort & Visual Editor
  • Past Purchases v2 API
  • Best Sellers v2 API


Experience-Driven Recommendations

This is the key feature and a game-changer when it comes to the Bloomreach Recommendations product. The feature will help you to deliver unique 1:1 personalised shopping experiences by creating real-time user affinity profiles and understanding user intent by leveraging the Bloomreach AI-driven Search Intelligence and user site-browsing behavior.

Experience-Driven Recommendations is a form of personalization and forms a strong addition to our personalization offering which includes Targeting, 1:1 Personalization and Relevance by Segment.

The ability to personalise and to understand the user shopping intent by analysing the search and browsing behaviour in real-time is a unique Bloomreach offering. Adding search intelligence to the recommendations engine dramatically improves the quality of Recommendations and therefore leads to higher revenue.


Analytics for Recommendations / Widget Analytics  

With Experience-Driven Recommendations, Bloomreach is releasing the first analytics reports for the Recommendations and Pathways product. The Overall Performance Report lets you analyze the widget performance by evaluating metrics like Revenue, Conversions, ATC, etc. 


Algorithm Improvements – Neural Embedding

In order to further improve the performance and relevance of the product recommendations, Bloomreach has developed a new AI model based on “Neural Embedding”. The new model is live and productized utilising a highly scalable best-in-class distributed computing stack and ML libraries. Neural Embedding improves coverage and relevance and makes Recommendations more powerful out of the box. 


UI Enhancements – Numeric Sort & Visual Editor

Bloomreach has made a lot of UI enhancements to improve the overall experience and ease of use. The Visual Editor experience is now more stable and consistent with the Preview experience. 

Along with the fixes and enhancements, we also added new functionality to sort recommendations based on Numeric Attributes. The feature is added for Recommendation Algorithms in the Dashboard.  


Past Purchases & Best Sellers v2 API

The Past Purchases & Best Seller API is now available as Recommendations V2 API and can be configured from the Recommendations Widget configurator. 


This marks a major milestone for personalization and the Bloomreach Recommendations product. By creating a unique, new user profile, connecting Recommendations to the powerful semantic understanding of products, Bloomreach looks at product-attribute affinity and search behavior, and relevance by segment to drive more revenue.

Ready to give it a try? Reach out for a demo of Bloomreach Recommendations today.



Niklas Winkels

Product Marketing Manager at Bloomreach

Niklas is a Product Marketing Manager and Developer Relations Expert with a background in Demand Generation.

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