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[{"key": "dc.contributor.advisor", "value": "Salonen, Anna", "language": null, "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Westr\u00e9n-Doll, Niklas", "language": null, "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2024-09-02T14:22:29Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2024-09-02T14:22:29Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2024", "language": null, "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/96904", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "T\u00e4m\u00e4 pro gradu -tutkielma k\u00e4sittelee teko\u00e4lyn avulla tuotettua personoitua markkinointia ja sen suhdetta kuluttajien tietoturvaan ja yksityisyyteen. Tutkimuksen tavoitteena on lis\u00e4t\u00e4 ymm\u00e4rryst\u00e4 siit\u00e4, kuinka teko\u00e4lyll\u00e4 voidaan tehostaa personoitua markkinointia, ja miten t\u00e4m\u00e4n k\u00e4yt\u00e4nn\u00f6n mahdollisuudet ja rajoitukset peilautuvat tietosuoja-asetuksiin sek\u00e4 kuluttajien yksityisyytt\u00e4 koskeviin asenteisiin. Aikaisemmassa personalisointia k\u00e4sitteleviss\u00e4 tutkimuksissa on sivuttu hieman teko\u00e4lyn integraation eri aspekteja, mutta kuluttajien yksityisyytt\u00e4 ei ole tarkasteltu yht\u00e4 merkitt\u00e4v\u00e4n\u00e4 osana t\u00e4t\u00e4 kehityst\u00e4. T\u00e4m\u00e4n vuoksi on tarpeen tarkastella n\u00e4it\u00e4 kolmea aihetta kattavasti yhdess\u00e4.\n\nTutkimuksessa k\u00e4ytettiin kvalitatiivista l\u00e4hestymistapaa, ja aineisto ker\u00e4ttiin puolistrukturoiduilla yksil\u00f6haastatteluilla. Aineistonkeruu toteutettiin huhti-toukokuussa 2024, ja osallistujat koostuivat kuudesta markkinointialan teko\u00e4lyasiantuntijasta. Aineiston analyysi toteutettiin abduktiivisen l\u00e4hestymistavan mukaisella temaattisella analyysill\u00e4.\n\nTutkimustulokset korostavat monia keskeisi\u00e4 n\u00e4k\u00f6kohtia teko\u00e4lyll\u00e4 ohjatusta personoidusta markkinoinnista. Teko\u00e4ly parantaa kohdennettua markkinointia hy\u00f6dynt\u00e4m\u00e4ll\u00e4 datal\u00e4ht\u00f6isi\u00e4 johtop\u00e4\u00e4t\u00f6ksi\u00e4 ja k\u00e4sityksi\u00e4 kuluttajak\u00e4ytt\u00e4ytymisen ennustamiseen ja ymm\u00e4rt\u00e4miseen, luoden n\u00e4in r\u00e4\u00e4t\u00e4l\u00f6idympi\u00e4 ja relevantimpia osto- ja asiakas-kokemuksia. Teko\u00e4lypersonoinnin tehokkuus kuitenkin riippuu eettisest\u00e4 datankeruusta ja kuluttajan yksityisyytt\u00e4 koskevista suojatoimista. Rakenteettoman datan merkityksen kasvaessa nousevat esiin uudenlaiset haasteet datavaihdon suostumuksen ja tekij\u00e4noikeuksien osalta. Lis\u00e4ksi yritysten sis\u00e4iset datasiilot ja tiukat GDPR-s\u00e4\u00e4d\u00f6kset vaikeuttavat teko\u00e4lypohjaisen personoinnin kehitt\u00e4mist\u00e4, mik\u00e4 osaltaan korostaa yrityskulttuurin ja johdon roolia yksityisyydensuojan varmistamisessa. Tutkimus korostaa my\u00f6s inhimillisten virheiden merkitt\u00e4v\u00e4\u00e4 vaikutusta datan kategorisoinnissa personointialgoritmeihin, laajentaen teoreettista ymm\u00e4rryst\u00e4 teko\u00e4lyll\u00e4 ohjatun markkinoinnin harhoista. Tulevat tutkimukset, jotka keskittyv\u00e4t enemm\u00e4n n\u00e4ihin n\u00e4k\u00f6kohtiin mahdollisesti muissa konteksteissa, voivat tarjota uusia n\u00e4kemyksi\u00e4 personoidun markkinoinnin kehitt\u00e4miseen ja hallitsemiseen teko\u00e4lyn aikakaudella.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "This master's thesis examines AI integrated marketing personalization and its relationship to consumer privacy. The aim of the research is to enhance understanding on how personalized marketing is made more effective with the use of AI, and how are the possibilities and limitations of the practice reflected on current data regulations and consumer attitudes about privacy. Previous research on personalization has slightly touched on AI integration but has not considered consumer privacy as a significant part of this development. Therefore, it was deemed necessary to examine the three subjects comprehensively.\n\nThe study employed a qualitative approach, collecting data through semi-structured individual interviews. Data collection was conducted in April-May of 2024, involving six experts in marketing AI. Data analysis was conducted through an abductive thematical analysis approach. \n\nThe research findings highlight many key aspects of AI-driven personalized marketing. AI enhances targeted marketing by leveraging data-driven insights to predict and understand consumer behaviors, creating more tailored and relevant experiences. However, the effectiveness of AI personalization depends on ethical data collection and privacy measures, with a rising importance of unstructured data introducing new challenges for consent and copyright. Additionally, data silos within companies and strict GDPR regulations hinder the development of AI-powered personalization, emphasizing the role of company culture and leadership in ensuring privacy compliance. The study also underscores the significant impact of human error in data categorization on personalization algorithms, expanding the theoretical understanding of biases in AI-driven marketing. Future studies focusing more on these aspects possibly in other contexts could offer new insights for the development and control of personalized marketing in the era of artificial intelligence.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by jyx lomake-julkaisija (jyx-julkaisija.group@korppi.jyu.fi) on 2024-09-02T14:22:29Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2024-09-02T14:22:29Z (GMT). No. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "82", "language": null, "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "CC BY 4.0", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.title", "value": "The computer knows best: AI-powered personalization in marketing through the lens of data privacy", "language": null, "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-202409025787", "language": null, "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Jyv\u00e4skyl\u00e4 University School of Business and Economics", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Jyv\u00e4skyl\u00e4n yliopiston kauppakorkeakoulu", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Marketing", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Markkinointi", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.copyright", "value": "\u00a9 The Author(s)", "language": null, "element": "rights", "qualifier": "copyright", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "masterThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.format.content", "value": "fulltext", "language": null, "element": "format", "qualifier": "content", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://creativecommons.org/licenses/by/4.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}]
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