{"id":4152,"date":"2025-02-06T08:03:45","date_gmt":"2025-02-06T16:03:45","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/semantic-kernel\/?p=4152"},"modified":"2025-02-06T08:03:45","modified_gmt":"2025-02-06T16:03:45","slug":"customer-case-study-how-preezies-ai-shopping-assistant-is-reshaping-blue-bungalows-online-store","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/agent-framework\/customer-case-study-how-preezies-ai-shopping-assistant-is-reshaping-blue-bungalows-online-store\/","title":{"rendered":"Customer Case Study: How preezie\u2019s AI shopping assistant is reshaping Blue Bungalow\u2019s online store"},"content":{"rendered":"<h1><span style=\"font-weight: 500;\">Introduction<\/span><\/h1>\n<p><span style=\"font-weight: 400;\">Blue Bungalow, one of Australia\u2019s leading fashion retailers, faced a common challenge in eCommerce\u2014how to create a more engaging, seamless, and personalised shopping experience for customers online. They wanted to implement AI-powered assistance to provide personalised product recommendations, accurate sizing guidance, product comparisons, and instant answers to customer questions\u2014replicating the ease and support of an in-store shopping experience. To bring this vision to life, preezie developed an AI shopping assistant, built on <\/span><b>Semantic Kernel<\/b><span style=\"font-weight: 400;\"> and <\/span><b>Elasticsearch<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><iframe title=\"\ud83e\udd16 preezie&#039;s AI shopping assistant is now more versatile than ever! \ud83d\udc4f\ud83c\udffd\ud83d\udecd\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/XCaw0LhJLhU?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><\/p>\n<h1><span style=\"font-weight: 500;\">The challenge: Enhancing the online shopping experience<\/span><\/h1>\n<p><span style=\"font-weight: 400;\">Blue Bungalow faced several key challenges in improving customer engagement:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Navigating a large product catalogue<\/b><span style=\"font-weight: 400;\"> \u2013 Customers needed an efficient way to quickly find relevant products.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Enhancing customer support<\/b><span style=\"font-weight: 400;\"> \u2013 Frequently asked product-related queries risked overwhelming human support teams.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Improving product discovery<\/b><span style=\"font-weight: 400;\"> \u2013 Customers often spent time searching for alternatives, similar styles, or comparative options.<\/span><\/li>\n<\/ul>\n<h1><span style=\"font-weight: 500;\">The solution: preezie\u2019s AI shopping assistant<\/span><\/h1>\n<p><span style=\"font-weight: 400;\">preezie developed a conversational AI assistant that acts as a virtual shopping guide. The solution is powered by Semantic Kernel, a framework that enables AI-driven orchestration and automation, making the assistant more intelligent and adaptive.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The AI assistant enhances Blue Bungalow\u2019s website with the following functionalities:<\/span><\/p>\n<h2><span style=\"font-weight: 500;\">1. Intelligent search and discovery<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">The assistant enables users to search for products using natural language processing (NLP). Semantic Kernel plays a crucial role in interpreting search intent and retrieving relevant results. Customers can interact with the AI as if they were speaking to a real person, using queries like:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">&#8220;Show me floral dresses for summer.&#8221;<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">&#8220;Find me a red evening dress under $100.&#8221;<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">&#8220;I need shoes that match this outfit.&#8221;<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">The system then queries Elasticsearch to fetch the most relevant results, while Semantic Kernel refines responses by incorporating contextual understanding and reasoning.<\/span><\/p>\n<h2><span style=\"font-weight: 500;\">2. Finding similar products<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">A core feature of the AI assistant is its ability to suggest alternatives that closely match customer preferences. Semantic Kernel enhances similarity detection by leveraging embeddings and contextual analysis, ensuring that recommended products align with individual shopping behaviours.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The assistant can:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Retrieve similar items based on colour, style, and price.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Offer substitutes when an item is unavailable.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Provide visually similar products using integrated image recognition models.<\/span><\/li>\n<\/ul>\n<h2><span style=\"font-weight: 500;\">3. Product comparisons<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">To help shoppers make informed purchasing decisions, the AI assistant enables side-by-side product comparisons. Powered by Semantic Kernel, it dynamically structures and summarizes key attributes, allowing users to:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">See key differences in fabric, fit, and price.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Review customer feedback and ratings in a clear, easy-to-digest format.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Explore alternatives across different price ranges, ensuring they find the best option within their budget.<\/span><\/li>\n<\/ul>\n<h1><span style=\"font-weight: 500;\">Technology stack<\/span><\/h1>\n<p><span style=\"font-weight: 400;\">preezie\u2019s AI shopping assistant is powered by a cutting-edge tech stack designed for speed, intelligence, and scalability:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Semantic Kernel<\/b><span style=\"font-weight: 400;\"> \u2013 The core framework orchestrating AI-powered interactions, enabling contextual understanding and advanced automation.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Elasticsearch<\/b><span style=\"font-weight: 400;\"> \u2013 A vector database that powers fast, relevant, and precise product searches.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>C# and .NET Core<\/b><span style=\"font-weight: 400;\"> \u2013 Ensuring a high-performance, scalable backend infrastructure.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Azure<\/b><span style=\"font-weight: 400;\"> \u2013 Providing robust cloud infrastructure and leveraging OpenAI models for enhanced AI capabilities.<\/span><\/li>\n<\/ul>\n<h1><span style=\"font-weight: 500;\">Impact and results<\/span><\/h1>\n<p><span style=\"font-weight: 400;\">The implementation of preezie\u2019s AI shopping assistant led to significant improvements in customer engagement and conversions on Blue Bungalow\u2019s website. Comparing customers who interacted with the AI assistant to those who did not, the following results were observed:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u23f3 <\/span><b>Time spent on site:<\/b><span style=\"font-weight: 400;\"> Doubled among AI-engaged customers.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\ud83d\uded2 <\/span><b>Add-to-cart rate: <\/b><span style=\"font-weight: 400;\">40% higher among AI-engaged customers.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\ud83d\udcc8 <\/span><b>Conversion rate:<\/b><span style=\"font-weight: 400;\"> Increased by 85% to 110% among AI-engaged customers.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\ud83d\udcb0<\/span><b> Average Order Value (AOV)<\/b><span style=\"font-weight: 400;\">: 7% higher among AI-engaged customers.<\/span><\/li>\n<\/ul>\n<h1><span style=\"font-weight: 500;\">Demo of our AI shopping assistant<\/span><\/h1>\n<p><a href=\"https:\/\/www.youtube.com\/watch?v=XCaw0LhJLhU\"><span style=\"font-weight: 400;\" data-rich-links=\"{&quot;fple-t&quot;:&quot;\ud83e\udd16 preezie's AI shopping assistant is now more versatile than ever! \ud83d\udc4f\ud83c\udffd\ud83d\udecd&quot;,&quot;fple-u&quot;:&quot;https:\/\/www.youtube.com\/watch?v=XCaw0LhJLhU&quot;,&quot;fple-mt&quot;:null,&quot;type&quot;:&quot;first-party-link&quot;}\">\ud83e\udd16 preezie&#8217;s AI shopping assistant is now more versatile than ever! \ud83d\udc4f\ud83c\udffd\ud83d\udecd<\/span><\/a><\/p>\n<h1><span style=\"font-weight: 500;\">Conclusion<\/span><\/h1>\n<p><span style=\"font-weight: 400;\">The preezie AI Shopping Assistant has transformed the online shopping experience for Blue Bungalow, enhancing customer engagement, product discovery, and sales conversions. Powered by Semantic Kernel, this AI-driven solution delivers hyper-personalised product recommendations, precise size guidance, and seamless product comparisons\u2014helping shoppers browse, compare, and buy with confidence, all in real-time.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As preezie continues to push the boundaries of AI in e-commerce, Semantic Kernel remains a core pillar of its innovation strategy. Looking ahead, preezie is excited to explore new capabilities that will further enhance the preezie AI platform, making online shopping even more intuitive, personalised, and engaging<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Introduction Blue Bungalow, one of Australia\u2019s leading fashion retailers, faced a common challenge in eCommerce\u2014how to create a more engaging, seamless, and personalised shopping experience for customers online. They wanted to implement AI-powered assistance to provide personalised product recommendations, accurate sizing guidance, product comparisons, and instant answers to customer questions\u2014replicating the ease and support of [&hellip;]<\/p>\n","protected":false},"author":149071,"featured_media":2302,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[42],"tags":[48,63,86,9],"class_list":["post-4152","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-customer-story","tag-ai","tag-microsoft-semantic-kernel","tag-preezie","tag-semantic-kernel"],"acf":[],"blog_post_summary":"<p>Introduction Blue Bungalow, one of Australia\u2019s leading fashion retailers, faced a common challenge in eCommerce\u2014how to create a more engaging, seamless, and personalised shopping experience for customers online. They wanted to implement AI-powered assistance to provide personalised product recommendations, accurate sizing guidance, product comparisons, and instant answers to customer questions\u2014replicating the ease and support of [&hellip;]<\/p>\n","_links":{"self":[{"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/posts\/4152","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/users\/149071"}],"replies":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/comments?post=4152"}],"version-history":[{"count":0,"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/posts\/4152\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/media\/2302"}],"wp:attachment":[{"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/media?parent=4152"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/categories?post=4152"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/agent-framework\/wp-json\/wp\/v2\/tags?post=4152"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}