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      E-Commerce Site Search and Merchandising

      Why Self-Learning AI Is a Game Changer in E-Commerce and Beyond

      By Kait Spong

      Apr 01, 2022

      11 min read

      E-Commerce Site Search and Merchandising

      Why Self-Learning AI Is a Game Changer in E-Commerce and Beyond

      Welcome to part two of our “Discovering Bloomreach Discovery” series, where we discuss the ins and outs of Bloomreach Discovery, as well as best practices, insights, and tips on intelligent product search, strategic merchandising, intuitive recommendations, and automated SEO.

      The early days of artificial intelligence (AI) weren’t as shiny or sleek as our science fiction movie favorites would lead us to believe. But it’s no wonder these depictions are so heavily ingrained in our imaginations since humans have been mulling over the idea of the mechanical man since the days of the early mathematicians, theologians, and philosophers.

      Being captivated with the idea of artificial intelligence has worked in our favor, though. Fast-forward to 2010, and AI very clearly became embedded in our day-to-day lives. Smartphones started coming pre-packaged with AI-driven capabilities, from facial recognition features to apps with global localization. Soon enough, virtual assistants like Siri, Alexa, and Google transformed into household names synonymous with convenience and productivity. And, before we knew it, cars were driving themselves, and you could enter the virtual world through a headset. 

      As you can probably see by now (if you haven’t already), AI is quite the umbrella term, and its meanings are so diverse and complex that they can often be lost or even taken for granted. To overcome this misunderstanding, it’s crucial to grasp how AI breaks down into multiple types, applications, and tasks. Ready to take a deep dive into the world of AI? Here are some basic questions we’ve answered that can help you understand what artificial intelligence can do for your business, specifically for your e-commerce site search.

      What Are the Most Common Applications of AI?

      From automotive and banking to healthcare and manufacturing, AI fills in voids that businesses experience every day. Whether it’s supplementing people or processes, AI can be very helpful across departments — think customer service, marketing, or sales. Yet, all the various ways AI can be segmented and used effectively are a bit mind-boggling, making it intimidating to get started. First, you’ll have to understand some of the most popular types of AI applications: 

      • Machine learning (ML) - ML focuses on the use of data and algorithms to mimic the way humans learn. The goal of ML is to gradually improve a machine’s accuracy over time, so it can supplement human labor on easy-to-automate tasks.
      • Natural Language Processing (NLP) - Similar to machine learning, natural language processing learns as time goes on. NLP concerns itself with understanding text and spoken word in the same ways humans can, as well as all the syntax, semantics, and characteristics that come along with it.
      • Robotics - Yes, it’s true. Robots are prevalent in AI. Robotics centers on the development of machines to accomplish tasks. Think of machinery that automates processes on a factory floor or in a fast food restaurant. 

      Which Businesses Are Currently Using AI Well?

      So, now that you better understand the applications of AI, let’s take a look at how businesses in today’s market are using it to their advantage. We see many strong examples across multiple sectors, including these few shining stars who are using the technology exceptionally well: 

      • Walmart - Walmart uses ML and image processing at all of its locations to keep its storefronts running smoothly and take the strain off of team members. With everything from weighted sensors and shelves to video cameras, Walmart’s AI can detect when products are running low or even if produce is starting to lose its quality to get a better sense of ordering patterns. 
      • UnitedHealth Group - This popular healthcare and insurance company deploys NLP to sort through the millions of calls they get to their customer service line each day and improve experiences. UnitedHealth Group is also no stranger to ML, using it to authorize payments for doctor-recommended medical procedures. 
      • Citigroup - Commonly known as Citi, this American multinational investment bank uses NLP to better understand customer activity. Since they operate in more than 160 countries, Citi wants to ensure that financial transactions are completed compliantly across the diversified geographies they represent within the confines of the law. 
      • HD Supply - HD Supply, one of the largest industrial distributors in North America, revamped its site search experience with self-learning AI algorithms that prioritized recall and ranking. With these changes in search, HD Supply experienced a 16% increase in revenue from search and a 4% increase in add-to-cart rate. 

      How Does AI Become Smarter Over Time?

      In the examples above, we talk a lot about self-learning AI that typically happens through ML and NLP. So, how does this “self-learning'' happen, exactly? Data and AI share a mutually beneficial relationship. AI can assist with data aggregation, storage, and retrieval, while data helps AI learn more and become increasingly efficient. Since there is a shortage of data scientists, AI can supplement and crunch large volumes of data coming from customer and prospect information, product catalogs, and business transactions. It’s a huge advantage in gathering deep analysis to improve decision making and assess goals and risks for your business.

      Where Can Self-Learning AI Step in With Search?

      Smart site search is one of AI’s most important contributions to the e-commerce sector. As the internet continues to refine itself, most businesses have come to realize that product discovery is just as important as the transaction. If your customers can’t find (or stumble upon) what they’re looking for, then how can they convert? 

      Enter self-learning AI, which can extract meaning from the titles and descriptions of your product catalog and words and phrases from your customer’s search queries to match their intent. After the retrieval process, it ranks your products and services appropriately — balancing learned ranking data with semantic relevance

      Beefing up your business' search bar with self-learning AI is one of the most significant steps you'll take when building personalized digital experiences. If done right, your team will notice improved conversion rates, revenue per visit (RPV), average order value (AOV), time to build a basket, and more.

      Let’s take a quick look at Staples, an American office retail company. The retailer sought to improve its digital experience and stay on top of market changes, such as the ongoing popularity of third-party marketplaces. Like HD Supply, Staples chose to focus more on its digital experience and implemented AI-powered site search with Bloomreach Discovery, leading to a 10-fold increase of two million stock-keeping units (SKUs) on its websites and a 3.5% lift in revenue. This revenue boost equated to over $100 million annually. 

      See what we mean? When the search bar does its job, you can drive conversions by guaranteeing your customers' relevant, personalized search results. Learn more about how self-learning AI can revamp your search bar, and check out an interactive tour of our Discovery offering today.          

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      Kait Spong

      Content Marketing Manager at Bloomreach

      Kait is a Content Marketing Manager at Bloomreach and has a passion for delving into the tech solutions B2B should deliver to their customers. Kait comes from an arts background, which is not unusual considering they call New Orleans home. Once earning their BA and MA in English, the seasoned writer delved into the world of content marketing, digital branding, search engine optimization, and social media marketing and has helped numerous businesses across all industries with their content and thought leadership strategies.

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