diplomsko delo
Abstract
V zadnjih letih smo priča hitremu razvoju informacijskih in spletnih tehnologij. Vse več se uporabljata izraza "informacijska družba" in "informacijska ekonomija", v kateri je podatek več vreden kot sami produkti in storitve. Podjetja zbirajo ogromne količine podatkov, ki jih s pomočjo podatkovnega rudarjenja obdelujejo in iz njih pridobivajo uporabne informacije, ki jih uporabljajo za načrtovanje poslovnih in marketinških strategij. V diplomskem delu smo obravnavali področja uporabe podatkovnega rudarjenja v elektronskem poslovanju. Ugotovili smo, da elektronsko poslovanje zaradi svojih lastnosti, predvsem prisotnosti na spletu, predstavlja učinkovito domeno za uspešno podatkovno rudarjenje. Osredotočili smo se predvsem na segmentacijo strank v elektronskem poslovanju, ki predstavlja jedro strategije upravljanja odnosov s strankami CRM. Predstavili smo prednosti, ki jih prinaša podatkovno rudarjenje v procesu segmentacije, ki se nanašajo predvsem na avtomatizacijo procesa in možnost personalizacije, ter opisali najbolj uporabljene tehnike in metode podatkovnega rudarjenja za segmentacijo strank. V empiričnem delu smo izvedli prikaz segmentacije strank spletne trgovine s pomočjo metode grozdenja k-means in LRFM modela, ki velja za enega najbolj učinkovitih modelov segmentacije strank na podlagi vedenja.
Keywords
podatkovno rudarjenje;elektronsko poslovanje;segmentacija strank;grozdenje;LRFM model;Diplomska dela;
Data
Language: |
Slovenian |
Year of publishing: |
2021 |
Typology: |
2.11 - Undergraduate Thesis |
Organization: |
UL FDV - Faculty of Social Sciences |
Publisher: |
[N. Nadu] |
UDC: |
005.336.1:004(043.2) |
COBISS: |
77365763
|
Views: |
460 |
Downloads: |
93 |
Average score: |
0 (0 votes) |
Metadata: |
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Other data
Secondary language: |
English |
Secondary title: |
Data mining and customer segmentation in e-commerce using the clustering method and LRFM model |
Secondary abstract: |
Over the last few years, we have witnessed the rapid development of information and web technologies. There is an increase in the use of the terms "information society" and "information economy" where data is valued more than the products and services themselves. Companies collect huge amounts of data which they process by means of data mining, and from which they obtain helpful information used to plan business and marketing strategies. In the thesis, we discussed the areas of application of data mining in electronic commerce. We found that e-commerce, due to its features, especially online presence, represents an effective domain for successful data mining. We focused mainly on customer segmentation in e-commerce which is the core of the CRM customer relationship management strategy. We presented the advantages of data mining in the segmentation process which relate mainly to process automation and the possibility of personalization, as well as described the most frequently used techniques and methods of data mining for customer segmentation. In the empirical part, we made a presentation of online store customer segmentation using the k-means clustering method and the LRFM model, which is considered to be one of the most effective behaviour-based customer segmentation models. |
Secondary keywords: |
Data Mining;E-Commerce;Customer Segmentation;Clustering;LRFM model;Podatkovno rudarjenje;Data mining;Elektronsko poslovanje;Electronic commerce;Trženje;Marketing;Graduate theses; |
Type (COBISS): |
Bachelor thesis/paper |
Study programme: |
0 |
Embargo end date (OpenAIRE): |
1970-01-01 |
Thesis comment: |
Univ. v Ljubljani, Fak. za družbene vede |
Pages: |
62 str. |
ID: |
13126619 |