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Mining changes in customer purchasing behavior: a data mining approach
2009 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The world around us is changing all the time. For businesses, knowing what is changing and how it has changed is also crucial. One of the most important aspects of surviving in a dynamic market is to know and adapt to changes happening in customer behavior. In Fast Moving Consumer Goods (FMCG) Distribution Company, this issue has more importance.Mining changes has several steps includes data collection, data preprocessing, customer segmentation, mining customer behavior patterns and change mining. For customer segmentation, we use Customer Value Matrix. For mining pattern of behavior, we use Apriori algorithm and maximal frequent itemsets. We have different kinds of changes based on the literature, added/perished rules, emerging pattern and unexpected changes. Also, there are two measures of similarity and unexpectedness to measure the change.

Place, publisher, year, edition, pages
2009.
Keyword [en]
Social Behaviour Law, Change mining, customer behavior, FMCG, data mining, association rules, BCG matrix
Keyword [sv]
Samhälls-, beteendevetenskap, juridik
Identifiers
URN: urn:nbn:se:ltu:diva-52716ISRN: LTU-PB-EX--09/097--SELocal ID: 9d1b7fd7-5ac8-459d-b118-18fc5d959a2dOAI: oai:DiVA.org:ltu-52716DiVA: diva2:1026088
Subject / course
Student thesis, at least 30 credits
Educational program
Electronic Commerce, master's level
Examiners
Note
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf