DC FieldValueLanguage
dc.contributor.authorDrivas, Ioannis-
dc.contributor.authorGiannakopoulos, Georgios-
dc.contributor.authorKyriaki - Manessi, Daphne-
dc.contributor.authorSakas, Damianos-
dc.date.accessioned2023-10-12T20:57:51Z-
dc.date.available2023-10-12T20:57:51Z-
dc.date.issued2021-01-01-
dc.identifierscopus-85109126927-
dc.identifier.isbn9783030570644-
dc.identifier.issn21987254-
dc.identifier.issn21987246-
dc.identifier.other85109126927-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/240-
dc.description.abstractIn the new era of marketing, being at the top results of search engines constitutes one of the most competitive advantages to the organizations’ overall online advertising strategy. In search engines, users type their search terms to cover their informational or purchasing needs and subsequently, search engines rank websites to the relevance of users’ search terms. The higher are the rankings of the websites, the more is the percentage of visitors who explicitly come from search engines. Nevertheless this obvious one marketing advantage, there is no prior research evidence as regards the level of engagement between users and content, after they visit the websites from search engines’ results. That is, users probably visit a website that comes at the top of search engines’ results, however, they do not spend an amount of time, or they do not browse in several webpages inside of it and vice versa. Against this backdrop, the authors proceed into the construction of a methodology composed of the retrieval of web analytics datasets and the development of computational models with the purpose to evaluate users’ engagement and content use within the websites. At the first stage, the authors proceed into the retrieval of web behavioral analytics at certain metrics for 125 sequential days as regards the time users are spending, the number of pageviews they are browsing, the percentage of immediate abandonments, and the percentage of traffic that explicitly comes from search engines. Following a data-driven methodological approach for the development of computational models, the fuzzy cognitive mapping at the descriptive modeling stage is adopted with the purpose to indicate the possible correlations between web analytics metrics. One step further, a corroborative and predictive model is proposed through the agent-based modeling method in order to compute the date ranges that resulted in the highest and the lowest engagements of users as regards the content of seven examined courseware websites. The proposed methodology and the results of this study work as a practical toolbox for decision makers while computing and evaluating through a data-driven way the level of engagement between visitors and the content they receive for online presence optimization on the web.en_US
dc.language.isoenen_US
dc.publisherSpringer Linken_US
dc.relation.ispartofBusiness Intelligence and Modellingen_US
dc.relation.ispartofseriesSpringer Proceedings in Business and Economicsen_US
dc.subjectAgent-based models in marketingen_US
dc.subjectBehavioral analyticsen_US
dc.subjectData-driven marketingen_US
dc.subjectSearch engine marketingen_US
dc.subjectWeb analyticsen_US
dc.subjectWebsites’ content engagementen_US
dc.subjectWebsites’ traffic evaluationen_US
dc.titleSearch Engines’ Visits and Users’ Behavior in Websites: Optimization of Users Engagement with the Contenten_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference on Business Intelligence & Modellingen_US
dc.identifier.doi10.1007/978-3-030-57065-1_3en_US
dc.identifier.scopus2-s2.0-85109126927-
dc.relation.deptDepartment of Archival, Library and Information Studiesen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.identifier.spage31en_US
dc.identifier.epage45en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeConference Paper-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0003-2407-9502-
crisitem.author.orcid0000-0002-1659-3504-
crisitem.author.orcid0000-0002-3310-6616-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου
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