Warenkorbanalysen mit Data Mining
AbstractWith increasing price-competition in retail business, marketing becomes the critical success factor. All activities have to be oriented towards customer needs. Within marketing research, the individual act of purchase plays a decisive role and necessitates a holistic analysis of the market basket. Moreover, progress in information technology has enabled us to store huge amounts of data, including a valuable pool of business experiences. It is not possible to make this potential knowledge completely available with conventional statistical approaches. This is where Data Mining provides an ideal approach. It is an analysis process for extracting information from large databases. The aim of the study, submitted as diploma thesis at the ETH Zurich, is to show a possible Data Mining Process for analyzing sales data in retail business. Thereby the analysis is focused on the efficiency of the process model and the identification of professional needs. According to Hippner, the Data Mining Process is applied systematically on the basis of a Market Basket Analysis. The Association Analysis, which detects relevant correlations between different products of an assortment, is the core of the process. Problems of interpreting identified association rules make a transformation into marketing recommendations very difficult. Nevertheless, the Data Mining Process turned out to be very efficient.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Swiss Society for Agricultural Economics and Rural Sociology in its journal Agrarwirtschaft und Agrarsoziologie/ Economie et Sociologie Rurales.
Volume (Year): (2005)
Issue (Month): 1 ()
Research Methods/ Statistical Methods; Agribusiness;
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.