Minería de datos para segmentación de clientes en la empresa tecnológica Master PC.

Data Mining applied in the field of marketing allows among other issues to discover behavior customer patterns that companies can use to develop marketing strategies directed towards their different types of customers. The grouping or clustering represents one of the most used mining techniques for this type of analysis, this technique is based on dividing a data set into smaller data segments or groups, where each segment contains similar data inside itself and maintains a marked difference from the other segments. This work has as a main objective to obtain Qualification customer segmentation in “Master PC “ technology company by applying Data Mining techniques, for this purpose it was taken into consideration the buying behavior of customers , which helped to identify the loyalty of Master PC technology company customers. The CRISP-DM methodology for Data Mining process was applied. The analysis was performed on the model RFM (Recency, Frequency, and Monetary), and over this model, clustering algorithms were applied: k-means, k-medoids, and Self-Organizing Maps (SOM). To evaluate the results of the algorithms, a classification algorithm was used. Finally Apriori algorithm was used to find associations between products for each customer group. The tool used for Data Mining process was the RStudio

• 主要作者: Chamba Jiménez, Sairy Fernanda. (author)
• 格式: bachelorThesis
• 语言: spa
• 出版: 2016
• 主题: <TÉCNICA DE MINERÍA DE DATOS><METODOLOGÍA CRISP-DM><HERRAMIENTA RSTUDIO>; <RFM( RECENCIA, FRECUENCIA, VALOR MONETARIO)><ALGORITMOS DE CLUSTERING><K-MEANS>; <K-MEDOIDS><SELF-ORGANIZING MAPS (SOM)>
• 在线阅读: http://dspace.unl.edu.ec/jspui/handle/123456789/10462