Why Bloomreach’s Innovations in AI Are Recognized by Industry Analysts

Anirban Bardalaye
Anirban Bardalaye
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AI has always been a part of Bloomreach, and it’s been the driving force behind our products since the very beginning. Our AI — Loomi — was built with ecommerce use cases and challenges in mind, and it’s what allows us to deliver impactful product discovery, merchandising, and more. 

Given that we power 25% of the world’s ecommerce, we’re constantly evaluating this data to identify additional areas of value for our customers. That’s why, with the rise of generative AI — and the unprecedented pace of technological transformation that came with it — we’ve been able to unlock incredible opportunities to innovate with AI. 

As a result, Bloomreach has been recognized as a Leader in the 2024 Gartner® Magic Quadrant™ for Search and Product Discovery and a Leader by Forrester over the past year. Learn more about our recent distinctions and how AI helped us get here. 

Bloomreach Receives Industry Recognition 

We’ve done some amazing work with AI in product discovery over the last few years, and we believe that is the reason for our industry recognitions. 

We’ve recently been recognized as a Leader in the 2024 Gartner® Magic Quadrant™ for Search and Product Discovery. Gartner evaluated Bloomreach for our product Bloomreach Discovery in the report. 

Meanwhile, we were also named a Leader in The Forrester Wave™: Commerce Search and Product Discovery, Q3 2023. Forrester had this to say about Bloomreach Discovery in their writeup: 

“Bloomreach balances broad functionality with modular architecture. Bloomreach is a well-established player in this market that continues to acquire and internally innovate. Its strong vision puts the merchandiser at the center of its strategic decisions.” 

Taking Product Discovery to the Next Level 

How did we manage to be recognized by industry analysts? It all comes down to generative AI. Generative AI advancements have allowed us to take advantage of technologies like two-tower neural networks and large language models (LLMs) to greatly scale up the way we train AI models. This, in turn, has also sped up our ability to enhance product discovery and create truly personalized experiences. 

One of our latest ways of introducing LLMs into product discovery is a feature we call LLM-based precision. At a high level, this is a way to reduce noise in your search results. Traditionally, this common problem has been solved by leveraging pixel data and intelligent ranking strategies, but that doesn’t work for every query. By leveraging LLMs and their superior contextual understanding, we can now solve this in a pixel-less way. The results for customers are already staggering. One brand saw its average CVR increase from 4% to 7%, its search bounce rate decrease by 2-3% points, and its search RPV increase by 25% — all within seven days of turning on the feature. These results are just from applying LLM to one specific area of search recall, and we see many more ways to incorporate it across all of product discovery.

Another AI-powered feature we’ve introduced is real-time segments. As customers take actions on the site — even if it’s their first visit — Loomi learns from that behavior and updates search results in real time to match their preferences. Loomi essentially looks at your audience segments and then trains itself on the dataset so it can build personalized rankings for each segment. 

Let’s say a customer searches for “jackets” on your site. That first search may lead to a wide range of results. But as the customer views items and makes additional search queries, Loomi will take that info, along with any other relevant customer data it’s analyzed, and make updates within milliseconds to match those preferences. So if this customer is in the UK and likes hiking — the results they see for jackets will end up being very different from, say, a customer in Australia who likes cycling. 

Our innovations with AI are what make this level of personalization possible, and it’s also opened up new avenues for personalization, like our recently released “Shop the Look” feature. This feature allows shoppers to upload an image and get personalized product recommendations — without needing to type a single word. Loomi can process visual data for fashion catalogs, extract the right product information, and then instantly serve up products with similar attributes, representing a huge leap forward in how AI can deliver seamlessly personalized experiences for consumers.

 

We’ve made incredible strides in using AI to improve the online shopping experience, and it’s an honor to have these innovations recognized by such authoritative voices in the industry. And as I mentioned earlier, we’re always on the search for new ways to bring value to our customers. We have some exciting innovations coming out that will continue to set us apart from other solutions on the market — follow along to stay up to date.

Gartner, Magic Quadrant for Search and Product Discovery, Mike Lowndes, Aditya Vasudevan, 13 May 2024

GARTNER is a registered trademark and service mark of Gartner and Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Bloomreach.

Gartner does not endorse any vendor, product, or service in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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Anirban Bardalaye

Chief Product Officer, Bloomreach

Anirban Bardalaye leads the development and execution of strategy to accelerate the growth of Bloomreach’s product pillars — Discovery, Engagement, and Content. Prior to joining Bloomreach, Anirban served as Vice President of Product Management, Commerce Cloud, at Salesforce. He holds an MBA from the University of Chicago Booth School of Business, a dual MS in Systems Science and Mechanical Engineering from Louisiana State University, and a BE in Mechanical Engineering from National Institute of Technology, Rourkela.

 

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