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Consequently, Customer Relationship Management solutions have been enhanced by means of several technologies to better understand the behaviour and requirements of customers, engaging and influencing them to improve their shopping experience, as well as increasing the retailers\u2019 profitability. Current solutions on marketing provide a too general approach, pushing and suggesting on most cases, the popular or most purchased items, losing the focus on the customer centricity and personality. In this paper, a recommendation system for fashion retail shops is proposed, based on a multi clustering approach of items and users\u2019 profiles in online and on physical stores. The proposed solution relies on mining techniques, allowing to predict the purchase behaviour of newly acquired customers, thus solving the cold start problems which is typical of the systems at the state of the art. The presented work has been developed in the context of Feedback project partially founded by Regione Toscana, and it has been conducted on real retail company Tessilform, Patrizia Pepe mark. The recommendation system has been validated in store, as well as online.<\/jats:p>","DOI":"10.1007\/s11042-021-11837-5","type":"journal-article","created":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T19:03:50Z","timestamp":1642100630000},"page":"9989-10016","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":60,"title":["Multi Clustering Recommendation System for Fashion Retail"],"prefix":"10.1007","volume":"82","author":[{"given":"Pierfrancesco","family":"Bellini","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luciano Alessandro Ipsaro","family":"Palesi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1044-3107","authenticated-orcid":false,"given":"Paolo","family":"Nesi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gianni","family":"Pantaleo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,1,13]]},"reference":[{"key":"11837_CR1","doi-asserted-by":"crossref","unstructured":"Agrawal R, Imielinski T and Swami A (1993) Mining association rules between sets of items in large databases ACM SIGMOD Rec., 22 (2):207\u2013216","DOI":"10.1145\/170036.170072"},{"key":"11837_CR2","unstructured":"Agrawal R, and Srikant R (1994) Fast algorithms for mining association rules in large databases. 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