Improving User Experience in E-commerce Through Intelligent Demand Forecasting and Inventory Visualization

Improving User Experience in E-commerce Through Intelligent Demand Forecasting and Inventory Visualization | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Improving User Experience in E-commerce Through Intelligent Demand Forecasting and Inventory Visualization Xue Song This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6197935/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract E-commerce has grown significantly, creating an urgent need for businesses to enhance user experience. This paper proposes innovative strategies to achieve this through intelligent demand forecasting and inventory visualization. We introduce a system that leverages historical sales data alongside current market trends to deliver more accurate demand predictions. By implementing machine learning algorithms, retailers can proactively anticipate customer needs, thereby optimizing their stock levels and minimizing the chances of stockouts. Complementing this, an interactive inventory visualization tool is presented, enabling users to track stock availability in real-time. This tool not only supports retailers in making data-driven decisions but also fosters customer satisfaction by ensuring products are accessible. Experimental results from e-commerce platforms illustrate that our approach significantly boosts customer engagement and enhances sales performance, emphasizing the critical role of advanced analytics in transforming the e-commerce environment for improved user experiences. Computer Architecture and Engineering User Experience Series Forecasting Interactive Visualization Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6197935","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":426868651,"identity":"f659b8da-1446-47a6-9ca7-0b98a3b656a0","order_by":0,"name":"Xue Song","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYNCCCjkInUC8ljPGQIKZFC2MbVAtRAGD84ePPfw6z0DenP38wQ8P/jDI84sdwK9FckZaurHsNgPDnT3JzBKJbQyGM2cTcB6/BI+ZtOS2P4wbDiSzMSQ2MCQY3CaghY3/DFDLHAP7DecfszEk/CFCCz9DjpnkxwaDxA03gLYksBGhBeiXNGmGYwbJG248Ngb6RYKwX0AhJvmjxsB2w/nEhx9//LGR55cmoAUEmHkQbAnCykGA8Qdx6kbBKBgFo2CkAgA/CT+Tzm3AMwAAAABJRU5ErkJggg==","orcid":"","institution":"Fanatcis","correspondingAuthor":true,"prefix":"","firstName":"Xue","middleName":"","lastName":"Song","suffix":""}],"badges":[],"createdAt":"2025-03-10 18:47:21","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6197935/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6197935/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78320141,"identity":"eecfb4a3-6754-44e9-a393-9a4c209489c7","added_by":"auto","created_at":"2025-03-12 04:53:51","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":554944,"visible":true,"origin":"","legend":"","description":"","filename":"ImprovingUserExperienceinEcommerceThrough.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6197935/v1_covered_65933842-ae4b-4db0-aa98-ad6d84e1d027.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eImproving User Experience in E-commerce Through Intelligent Demand Forecasting and Inventory Visualization\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Fanatcis","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"User Experience, Series Forecasting, Interactive Visualization","lastPublishedDoi":"10.21203/rs.3.rs-6197935/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6197935/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eE-commerce has grown significantly, creating an urgent need for businesses to enhance user experience. 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