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This paper analyzes AI and machine learning approaches used to estimate initial demand and refine forecasts using early interest signals. The analysis emphasizes the role of product metadata, similarity search, and external factors in practical performance. Method limitations relevant to campaign planning workflows are discussed, including reproducibility and data availability. Corporate case figures are treated as manufacturer-supplied and require independent validation.<\/jats:p>","DOI":"10.34925\/eip.2026.187.2.138","type":"journal-article","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T03:20:26Z","timestamp":1779333626000},"page":"802-808","source":"Crossref","is-referenced-by-count":0,"title":["\u041f\u0420\u0418\u041c\u0415\u041d\u0415\u041d\u0418\u0415 \u0418\u0421\u041a\u0423\u0421\u0421\u0422\u0412\u0415\u041d\u041d\u041e\u0413\u041e \u0418\u041d\u0422\u0415\u041b\u041b\u0415\u041a\u0422\u0410 \u0414\u041b\u042f \u041c\u0410\u0420\u041a\u0415\u0422\u0418\u041d\u0413\u041e\u0412\u041e\u0413\u041e \u041f\u0420\u041e\u0413\u041d\u041e\u0417\u0418\u0420\u041e\u0412\u0410\u041d\u0418\u042f \u0421\u041f\u0420\u041e\u0421\u0410 \u041d\u0410 \u041d\u041e\u0412\u042b\u0415 \u0422\u041e\u0412\u0410\u0420\u042b \u0412 \u042d\u041b\u0415\u041a\u0422\u0420\u041e\u041d\u041d\u041e\u0419 \u041a\u041e\u041c\u041c\u0415\u0420\u0426\u0418\u0418"],"prefix":"10.34925","author":[{"given":"\u0415.\u0412.","family":"\u041c\u0418\u0429\u0415\u041d\u041a\u041e","sequence":"first","affiliation":[{"name":"\u0420\u043e\u0441\u0441\u0438\u0439\u0441\u043a\u043e-\u0410\u0440\u043c\u044f\u043d\u0441\u043a\u0438\u0439 \u0423\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442"},{"name":"E-Commerce & Digital Marketing Association"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u041c.","family":"\u0427\u0415\u0420\u041a\u0410\u0421","sequence":"first","affiliation":[{"name":"\u0418\u041f \u0427\u0435\u0440\u043a\u0430\u0441"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u0410.\u0428.","family":"\u0410\u0419\u0414\u0410\u0420\u041e\u0412\u0410","sequence":"first","affiliation":[{"name":"\u041e\u041e\u041e \u0410\u0418 \u041c\u041e\u0421"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u041b.\u041a.","family":"\u0418\u042e\u041f\u041e\u0412\u0410","sequence":"first","affiliation":[{"name":"Easy Sound LLC"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u0414.\u0412.","family":"\u0410\u041b\u0415\u041a\u0421\u0415\u0415\u0412","sequence":"first","affiliation":[{"name":"Flodigit"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"50238","reference":[{"key":"1","unstructured":"Statista. 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Zheng [et al.] \/\/ arXiv:2506.06336. - 2025."}],"container-title":["\u042d\u043a\u043e\u043d\u043e\u043c\u0438\u043a\u0430 \u0438 \u043f\u0440\u0435\u0434\u043f\u0440\u0438\u043d\u0438\u043c\u0430\u0442\u0435\u043b\u044c\u0441\u0442\u0432\u043e"],"original-title":[],"language":"ru","deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T03:39:11Z","timestamp":1779334751000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.elibrary.ru\/item.asp?id=89207931"}},"subtitle":["APPLICATION OF ARTIFICIAL INTELLIGENCE FOR MARKETING DEMAND FORECASTING OF NEW PRODUCTS IN E-COMMERCE"],"short-title":[],"issued":{"date-parts":[[2026,3,24]]},"references-count":28,"journal-issue":{"issue":"2(187)","published-print":{"date-parts":[[2026,3,24]]}},"URL":"https:\/\/doi.org\/10.34925\/eip.2026.187.2.138","relation":{},"ISSN":["1999-2300"],"issn-type":[{"value":"1999-2300","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3,24]]}}}