Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Bloomreach Offers Marketers a No-code Feature for Testing AI-Powered, Personalized Product Recommendations

 Bloomreach, the world’s #1 Commerce Experience Cloud,announced an easier way for marketers using Bloomreach Engagement to test AI-powered product recommendations. This new feature enhancement gives marketers the ability to experiment with personalized recommendations on their website through an easy-to-use visual editor and template blocks that require no coding. Marketers from all technical skill levels can leverage Bloomreach Engagement’s A/B testing capabilities and website experiments without the help of IT, driving faster time-to-value and more revenue opportunities.

Recommended AI: The Future of AI Is Here. Now Let’s Make It Ethical

Personalization is key to engaging today’s consumer, who often expects their favorite brands to know what they want without being told. AI makes this possible, enabling marketers to deliver personalized product recommendations based on real-time customer data. Yet deploying and experimenting with these product recommendations can be difficult for marketers with less technical expertise, requiring coding knowledge or the assistance of IT teams.

The latest enhancement to Bloomreach Engagement’s web recommendations feature offers marketers a user-friendly solution for deploying and experimenting with personalized product recommendations for every customer. With predefined templates and an easy-to-use visual editor, Bloomreach’s advanced AI and machine learning algorithms can build product recommendations with the customer and their preferences at the forefront – making website personalization even more attainable for marketing teams.

Related Posts
1 of 37,179

Recommended AI: AiThority Interview with Jessica Kipper, Senior Director, Software Product Management at Schneider Electric

“This enhancement to our web recommendations feature is built for today’s marketers, who we know are eager to experiment with new ways to engage their customers. With the enhanced accessibility of a no-code solution, technical skill sets never have to stand in the way of bringing AI-powered personalization to life,” said Michal Novovesky, General Manager and Head of Product, Bloomreach Engagement. “We’re excited to see how our Engagement users will be able to unlock a new level of personalization and value for their customers.”

Recommended AI: AiThority Interview with Pete Wurman, Director at Sony AI

[To share your insights with us, please write to]

Comments are closed.