Subscribe

Filter

Explore by Category

    Explore by Tag

    Subtopic tags

      E-Commerce Site Search and Merchandising

      Drive Revenue and Better Search Results With Semantic Search

      By Shinhe Cho

      Jul 08, 2022

      9 min read

      E-Commerce Site Search and Merchandising

      Drive Revenue and Better Search Results With Semantic Search

      If you’re managing the e-commerce experience for your business or looking for revenue drivers with your online store, then you know how critical it is to get the search experience right. A smooth search experience — when a customer types a query into a site’s search bar and gets relevant results — is not only a win for customer experience but is also increasingly table stakes for most online shoppers and buyers

      That’s because site search is often a significant revenue driver for e-commerce businesses. For B2C sites, while only 15% of customers use site search, these searchers account for 45% of total online revenue. On the B2B side, 40% will use site search, accounting for 60% of total revenue. The implications are huge: When customers or buyers are searching on your commerce site, irrelevant results are hurting your bottom line, and your team might feel stuck when searching for solutions.

      At the same time, we know it’s not an easy fix. Optimizing search is hard because the way customers search is constantly changing, and search queries are not always mapped to product data. Other solutions, like e-commerce platform add-ons or homegrown/open-source tools, either don’t work or require too much time and resources. In addition, commerce search is a different beast than content search, with many solutions promising the former with technology built for the latter. 

      Here’s where true semantic understanding comes in. Semantic understanding uses AI to bring deep product and customer understanding directly into the search bar for improved relevance. For over 10 years, we have been the leaders in semantic understanding, enabling our machine-learning algorithms to intelligently parse customer queries, become an expert on product data, and return relevant, conversion-driving results — all without breaking a sweat. We are pleased to announce that this game-changing core capability is now available in French and German.

      It’s All “Just” Semantics

      But what is semantic understanding, exactly? In short, a search engine can process real-world language and decipher customer intent. When someone says they want to buy a “shirt dress,” for example, semantic understanding can tell that they’re looking for a dress, not a shirt.

      Many search engines in the market today leverage basic recall and ranking algorithms that rely on manually adjusted rules, which could lead to a search results page that would include both “shirt dress” and “dress shirt.” Or, if a search engine says it leverages AI-based algorithms, it often means they use AI for ranking, not recall — leading shoppers to a page of null results. 

      It all starts with Bloomreach’s semantic understanding technology built on several techniques under the larger umbrella of natural language processing (NLP). We’ve created an entity recognition engine to parse out "product types" and "product attributes" from product content and user query data. This data factors into a larger knowledge graph we’ve accumulated over the years, leading to an impressive synonym library that enables us to get “recall” right with every search

      Our automatic query relaxation also ensures that your customers never get a null or zero results page because our technology serves up the most relevant results for every query. As we've encountered a larger variety of customer content, we've continued to tune and enhance our semantic understanding algorithms. We're now able to parse even more complex data, such as numerical attributes and part-number search. 

      Today, many tech vendors claim to have semantic understanding included in their packages, but here’s how to tell if it’s true: Go to some of their customers’ sites and test their algorithms! Use these guides to give their technology a run for their money: 

      • Use variations of products you know they sell (e.g., “band-aids” versus “bandages” or “jacket” versus “jackets”)
      • Search for a brand you know they don’t sell (e.g., “Adidas sneakers” at a Nike store) 
      • Type in an expansive product line (e.g., search for “laptops” and sort by price to see how well the algorithm ranks products — are accessories coming up too soon?) 

      True Semantic Understanding Drives Bottom-line Results

      Now that you know what Bloomreach’s semantic search can do, what does this mean for your business? It’s no question that semantic understanding-based search is critical for a seamless customer experience. Not only does Bloomreach Discovery solve issues with product search with our best-in-class and AI-driven solution, but we also take it one step further. Our algorithms are specifically tuned to boost revenue per visitor (RPV). That means showing results that are helpful to the customer AND drive revenue for the business. See for yourself how our customers have succeeded using our site search module

      Get Started With Better Search Today

      With 27 registered patents related to e-commerce search, Bloomreach is the market leader in all things intelligence. See how much ROI you could begin immediately generating after investing in product search with Bloomreach Discovery, or check out our virtual demo to learn more. 

      Found this useful? Subscribe to our newsletter or share it.


      Shinhe Cho

      Product Marketing Manager

      Shinhe Cho connects customers to the magic of Bloomreach’s Discovery pillar of products as a Product Marketing Manager. A customer-centric product advocate, she enjoys delivering value and solving problems, one message at a time.

      Discover more content like this

      Ready to see Bloomreach in Action?

      Request Demo