{"id":10613,"date":"2025-06-23T08:30:00","date_gmt":"2025-06-23T06:30:00","guid":{"rendered":"https:\/\/www.fact-finder.com\/blog\/?p=10613"},"modified":"2025-08-12T10:09:00","modified_gmt":"2025-08-12T08:09:00","slug":"ecommerce-site-search-vector-search","status":"publish","type":"post","link":"\/blog\/ecommerce-site-search-vector-search\/","title":{"rendered":"Vector search: eCommerce site search made conversational"},"content":{"rendered":"\n<p><em>Online shopping is changing. Customers want your eCommerce site search to understand them, not just keywords. So, what if your solution could listen and give them the right results no matter how they phrase their query? Meet FactFinder\u2019s vector search.<\/em><\/p>\n\n\n\n<!--more-->\n\n\n\n<p>For over two decades, we\u2019ve conditioned ourselves to shop online using keywords, because that\u2019s all search could understand. It works, and with the right engine behind it, it converts. <a href=\"https:\/\/www.fact-finder.com\/landing-page\/video-llms-in-ecommerce.html\" target=\"_blank\" rel=\"noreferrer noopener\">But large language models (LLMs) like ChatGPT, Perplexity and Gemini, are influencing how people search.<\/a> More and more, buyers expect the right results from natural language and open-ended queries. eCommerce needs to keep up.<\/p>\n\n\n\n<p>This is where <a href=\"https:\/\/www.fact-finder.com\/products\/vector-search.html\">vector search<\/a> comes in. Our semantic search technology understands the context and meaning behind queries where pure keyword matching reaches its limits \u2014 for example, a descriptive search like <em>\u201chigh-performance laptop with plenty of storage for gaming\u201d<\/em>. While a good keyword-based search can pick out terms like \u201claptop,\u201d \u201cgaming\u201d and \u201cstorage,\u201d it often returns a mixed bag of devices and accessories \u2014 or even zero results \u2014 leaving the shopper without the gaming notebook they actually wanted.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"397\" src=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Vector_Search_consumer-electronics-eCommerce-site-search-1024x397.png\" alt=\"A simple diagram of vector search using nearest neighbor search to provide the most relevant results for the natural language query &quot;powerful laptop with a big memory for gaming&quot;\" class=\"wp-image-10658\" srcset=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Vector_Search_consumer-electronics-eCommerce-site-search-1024x397.png 1024w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Vector_Search_consumer-electronics-eCommerce-site-search-300x116.png 300w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Vector_Search_consumer-electronics-eCommerce-site-search-768x298.png 768w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Vector_Search_consumer-electronics-eCommerce-site-search.png 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>Vector search, on the other hand, recognizes the meaning and intent behind conversational, natural language queries and instantly shows the right products \u2014 even when there are no keyword matches. This cuts bounce rates, speeds up shopping time, improves the customer experience and wins you sales and brand loyalty. Read on to uncover the magic behind FactFinder\u2019s vector search \u2014 or hit play to watch the video walkthrough from our Vice President of Product and Technology, Holly Murdoch.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\" title=\"Meet vector search: eCommerce site search made conversational\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/69c-9ZmDHsI?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><a href=\"\/blog\/vector-search\/\" target=\"_blank\" rel=\"noreferrer noopener\">What is vector search?<\/a><\/h2>\n\n\n\n<p>Put simply, <a href=\"\/blog\/vector-search\/\" target=\"_blank\" rel=\"noreferrer noopener\">vector search works like a navigation system on a map<\/a>. In eCommerce, it turns search queries and products into numeric vectors, which act like coordinates. It then measures the distance between them using \u201cnearest neighbor search\u201d.<\/p>\n\n\n\n<p>The closer the product vector is to the query vector, the more relevant it is and the higher it ranks in the search results \u2014 even if the two don\u2019t share matching keywords in the product data.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"\/blog\/vector-search\/\" target=\"_blank\" rel=\" noreferrer noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"265\" src=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Dive_deeper_into_vector_search_Banner-1024x265.png\" alt=\"Dive into our blog post to learn the ins and outs of vector search in eCommerce and how it can increase conversion.\" class=\"wp-image-10645\" srcset=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Dive_deeper_into_vector_search_Banner-1024x265.png 1024w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Dive_deeper_into_vector_search_Banner-300x78.png 300w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Dive_deeper_into_vector_search_Banner-768x199.png 768w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Dive_deeper_into_vector_search_Banner.png 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Benefits of vector search<\/h2>\n\n\n\n<p>\u2714\ufe0f <strong>No more zero results<\/strong> \u2014 vector search brings semantic understanding to every query, helping customers find what they need even from vague and conversational language. No dead ends like with traditional search, and no manual optimizations required.<\/p>\n\n\n\n<p>\u2714\ufe0f <strong>More sales<\/strong> \u2014 thanks to customers finding the right products faster.<\/p>\n\n\n\n<p>\u2714\ufe0f <strong>Fewer bounces<\/strong> \u2014 customers stay engaged and inspired with relevant results from their first search.<\/p>\n\n\n\n<p>\u2714\ufe0f <strong>Smarter processing of unstructured data<\/strong> \u2014 less manual effort, huge time and cost savings and faster return on investment (ROI).<\/p>\n\n\n\n<p>\u2714\ufe0f <strong>Happier customers and higher lifetime value (LTV)<\/strong> \u2014 buyers are more likely to make repeat purchases and recommend you to other people.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What makes our vector search different?<\/h2>\n\n\n\n<p>Vector search has been a trending topic over the last year. So, what\u2019s different about FactFinder&#8217;s approach?<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\ud83d\udd12Based on our own in-house language model<\/h5>\n\n\n\n<p>Most other vector search models use online third party LLMs and language models. We use our own. That means we can keep our vector search database offline and in-house here in the EU, ensuring all data is kept 100% secure and private. No dodgy online or overseas transfers.<\/p>\n\n\n\n<p>Plus, we train the language model ourselves. With 20+ years of eCommerce site search expertise behind us, we make sure it delivers across real-world use cases. While other vector models are built for generic tasks, ours is made for online purchases. We can even train it for specific industries, so it picks up on specialized language and understands searches in context.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\ud83c\udf0d Special multilingual support<\/h5>\n\n\n\n<p>Most vector search models are only tested in English, showing questionable performance in other languages, which slows your global expansion. Ours breaks through that barrier, with <a href=\"\/blog\/berners-20-search-spike-with-factfinder\/\" target=\"_blank\" rel=\"noreferrer noopener\">proven success handling complex languages<\/a> like German and even multilingual queries like \u201crote handbag.\u201d This enables you to deliver a flawless search experience everywhere.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\ud83d\udd0e Backed with advanced keyword search<\/h5>\n\n\n\n<p>Vector search is great, but it\u2019s not always the best tool for the job. For exact matches, like product IDs or brand-name searches, keyword search often outperforms it. While keyword search shows only the specified item, <a href=\"\/blog\/vector-search\/\" target=\"_blank\" rel=\"noreferrer noopener\">vector search can return a mix of similar products<\/a> that distracts from what the customer actually wants.<\/p>\n\n\n\n<p>That\u2019s why <a href=\"https:\/\/www.fact-finder.com\/products\/product-discovery.html#:~:text=black%20box%20here.-,Core%20capabilities,-Our%20Product%20Discovery\" target=\"_blank\" rel=\"noreferrer noopener\">FactFinder blends advanced keyword search with vector capabilities<\/a> \u2014 so you get exact matches when needed, and smart results when keyword search fails.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u2699\ufe0f Flexible to fit your eCommerce strategy<\/h5>\n\n\n\n<p>No two eCommerce businesses are the same. Depending on your assortment, audience and strategy, every shop has its own unique requirements. We give you the flexibility to tailor this new technology to your use case, combining the strengths of vector and keyword search for the best possible customer experience. In the intuitive backend, you can choose between two modes:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Hybrid mode<\/strong> delivers a smart product list made up of both keyword-based and vector-based results. You can fine-tune the weighting between the two to match your strategy. This mode is ideal for audiences who often browse for inspiration, have limited product knowledge or shop for specific occasions, such as in <a href=\"https:\/\/www.fact-finder.com\/industries\/fashion.html\">fashion<\/a>, DIY or <a href=\"https:\/\/www.fact-finder.com\/industries\/beauty.html\">beauty<\/a>.<\/li>\n\n\n\n<li><strong>Fallback mode<\/strong> steps in only when keyword matching would return no results. Instead of landing on a zero-results page and potentially leaving, customers see all products that best match the meaning of their search. Perfect for <a href=\"https:\/\/www.fact-finder.com\/industries\/b2b-ecommerce.html\">technical B2B assortments where shoppers typically search for specific product variants or SKUs<\/a>, and where keyword search should take clear priority over semantic search.<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Vector search in action: applying vector to your eCommerce site search<\/h2>\n\n\n\n<p>Vector search can be powerful, especially when backed by keyword search. But will it work for your business? Let\u2019s take a look. Here are a few examples of how it performs across different industries.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\"><a href=\"https:\/\/www.fact-finder.com\/industries\/fashion.html\" target=\"_blank\" rel=\"noreferrer noopener\">Fashion<\/a><\/h5>\n\n\n\n<p>Fashion shoppers increasingly search with a feeling in mind instead of a product name. Take \u201coutfit for a first date\u201d \u2014 vague, emotional, and open to interpretation. Keyword search would likely miss the mark, but vector search understands the intent and maps the context to real products. The result? Higher engagement and more confident buying decisions.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter is-resized\"><a href=\"https:\/\/www.fact-finder.com\/industries\/fashion.html\" target=\"_blank\" rel=\" noreferrer noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"720\" src=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/01_Fashion-eCommerce-site-search_vector_search-1024x720.png\" alt=\"Screenshot showing a typical natural language query used in eCommerce site search engines: \u201coutfit for a first date\u201d. Keyword search would likely miss the mark, but vector search understands the intent and maps the context to real products. In this vector search example, the results show a relevant assortment of clothes, including a black dress, a playsuit, a summer dress, jeans, sneakers and heels.\" class=\"wp-image-10648\" style=\"width:800px\" srcset=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/01_Fashion-eCommerce-site-search_vector_search-1024x720.png 1024w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/01_Fashion-eCommerce-site-search_vector_search-300x211.png 300w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/01_Fashion-eCommerce-site-search_vector_search-768x540.png 768w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/01_Fashion-eCommerce-site-search_vector_search.png 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure><\/div>\n\n\n<h5 class=\"wp-block-heading\"><a href=\"https:\/\/www.fact-finder.com\/industries\/sporting-goods.html\" target=\"_blank\" rel=\"noreferrer noopener\">Sporting goods<\/a><\/h5>\n\n\n\n<p>Vector search comes in very handy for online shoppers taking up a new sport. Generally, they have an idea of what they need but not specific features. If someone searches for \u201ccute sneakers for a 5km park run,\u201d vector search catches the meaning and delivers breathable, supportive sneakers for cross-country running that look good.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><a href=\"https:\/\/www.fact-finder.com\/industries\/sporting-goods.html\" target=\"_blank\" rel=\" noreferrer noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"720\" src=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/02_sporting-goods-eCommerce-site-search_vector_screenshot-1024x720.png\" alt=\"Vector search in action on a hypothetical sporting goods online shop. An example of eCommerce site search results for the natural language query &quot;cute sneakers for 5km park run&quot; - keyword search alone would return 0 results, but here, vector search understands the meaning and shows a range of colorful, stylish sneakers designed for running outdoors on cross-country terrain\" class=\"wp-image-10651\" style=\"width:800px\" srcset=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/02_sporting-goods-eCommerce-site-search_vector_screenshot-1024x720.png 1024w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/02_sporting-goods-eCommerce-site-search_vector_screenshot-300x211.png 300w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/02_sporting-goods-eCommerce-site-search_vector_screenshot-768x540.png 768w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/02_sporting-goods-eCommerce-site-search_vector_screenshot.png 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure><\/div>\n\n\n<h5 class=\"wp-block-heading\"><a href=\"https:\/\/www.fact-finder.com\/industries\/food-beverage.html\" target=\"_blank\" rel=\"noreferrer noopener\">Food &amp; beverage<\/a><\/h5>\n\n\n\n<p>Many <a href=\"https:\/\/www.fact-finder.com\/industries\/food-beverage.html\" target=\"_blank\" rel=\"noreferrer noopener\">grocery shoppers<\/a> know their shopping list by heart, but when faced with a special occasion or looking for inspiration, they turn to the search bar for help. A query like \u201cvegan food for BBQ\u201d won\u2019t match product names directly, but vector search captures the implied requirements \u2014 plant-based products suitable for a barbecue \u2014 and suggests the perfect items.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><a href=\"https:\/\/www.fact-finder.com\/industries\/food-beverage.html\" target=\"_blank\" rel=\" noreferrer noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"720\" src=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Food-beverage-eCommerce-site-search_vector_results-1024x720.png\" alt=\"An example of a natural language eCommerce site search query used in food and beverage\/grocery stores: \u201cvegan food for BBQ\u201d and relevant results, including tofu, peppers\/capsicum, bean burgers, vegan sausages, zucchinis and mushrooms\" class=\"wp-image-10652\" style=\"width:800px\" srcset=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Food-beverage-eCommerce-site-search_vector_results-1024x720.png 1024w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Food-beverage-eCommerce-site-search_vector_results-300x211.png 300w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Food-beverage-eCommerce-site-search_vector_results-768x540.png 768w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/Food-beverage-eCommerce-site-search_vector_results.png 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure><\/div>\n\n\n<h5 class=\"wp-block-heading\"><a href=\"https:\/\/www.fact-finder.com\/industries\/b2b-ecommerce.html\" target=\"_blank\" rel=\"noreferrer noopener\">B2B eCommerce<\/a><\/h5>\n\n\n\n<p>If a <a href=\"https:\/\/www.fact-finder.com\/industries\/b2b-ecommerce.html\" target=\"_blank\" rel=\"noreferrer noopener\">B2B buyer<\/a> knows their needs but not which product, vector search can find the perfect match for their specific use cases. For example, queries like \u201cthermal insulation sleeve for electrical cables\u201d or \u201croller bearing 6205 with heat resistance,\u201d are mapped to relevant product features and categories, helping customers self-serve with confidence.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/www.fact-finder.com\/industries\/b2b-ecommerce.html\" target=\"_blank\" rel=\" noreferrer noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"720\" src=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/B2B-eCommerce-site-search_vector_results-1024x720.png\" alt=\"B2B eCommerce site search vector results for natural language query: thermal insulation sleeve for electrical cables\" class=\"wp-image-10662\" srcset=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/B2B-eCommerce-site-search_vector_results-1024x720.png 1024w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/B2B-eCommerce-site-search_vector_results-300x211.png 300w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/B2B-eCommerce-site-search_vector_results-768x540.png 768w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2025\/06\/B2B-eCommerce-site-search_vector_results.png 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Never miss a sale again with future-proof eCommerce vector search technology<\/h2>\n\n\n\n<p>Most people still search like keyword users. But that\u2019s changing fast. <a href=\"https:\/\/www.fact-finder.com\/landing-page\/video-llms-in-ecommerce.html\" target=\"_blank\" rel=\"noreferrer noopener\">Customers are moving toward smarter tech where apps understand natural language<\/a>. They don\u2019t need to use keywords with Google anymore. So why should they have to on your site?<\/p>\n\n\n\n<p>With our vector search, you\u2019re already aligned with the next generation of shopping \u2014 making it more intuitive and exceeding higher expectations. Smarter eCommerce site search means fewer missed moments and more confident purchases.<\/p>\n\n\n\n<p>Try our new vector search now. Hit the banner below to book a personalized demo and see what FactFinder can do for your business.<\/p>\n\n\n\n<p>Already a FactFinder customer? Just get in touch with your CSM or <a href=\"https:\/\/www.fact-finder.com\/request-demo.html\" target=\"_blank\" rel=\"noreferrer noopener\">contact us here<\/a> to try out vector search on your product data.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/www.fact-finder.com\/request-demo.html\" target=\"_blank\" rel=\" noreferrer noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"860\" height=\"223\" src=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2024\/01\/Demo_Banner_EN_01_Zeichenflache-1.png\" alt=\"Demo Banner EN 01 Zeichenflache 1\" class=\"wp-image-9273\" srcset=\"https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2024\/01\/Demo_Banner_EN_01_Zeichenflache-1.png 860w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2024\/01\/Demo_Banner_EN_01_Zeichenflache-1-300x78.png 300w, https:\/\/www.fact-finder.com\/blog\/wp-content\/uploads\/2024\/01\/Demo_Banner_EN_01_Zeichenflache-1-768x199.png 768w\" sizes=\"auto, (max-width: 860px) 100vw, 860px\" \/><\/a><\/figure>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Online shopping is changing. Customers want your eCommerce site search to understand them, not just keywords. So, what if your solution could listen and give them the right results no matter how they phrase their query? Meet FactFinder\u2019s vector search.<\/p>\n","protected":false},"author":51,"featured_media":10644,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[202,204],"tags":[199,25,27,41],"class_list":["post-10613","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-factfinder","category-retail-tips","tag-ecommerce","tag-online-shop","tag-search-2","tag-trends"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Vector search: eCommerce site search made conversational - FactFinder blog<\/title>\n<meta name=\"description\" content=\"Our eCommerce site search solution uses vector search to show spot-on results for natural language queries that keyword search can&#039;t handle.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.fact-finder.com\/blog\/ecommerce-site-search-vector-search\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Vector search: eCommerce site search made conversational - 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