Segmentation and Profiling using SPSS for Windows.ppt

Segmentation and Profiling using SPSS for Windows Kate Grayson Why Segmentation? Used by e.g. retail and consumer product companies Trying to learn about and describe their customers buying habits, gender, age, income level, etc. These companies tailor their marketing and product development strategies to each consumer group to increase sales and build brand loyalty. A valuable approach in Market Research, and SPSS offers some useful tools to facilitate this commercial process Segmentation in SPSS Most of the techniques for segmentation and profiling are exploratory There is no right or wrong answer, and the results are open to interpretation Trying to make sense of the data or find patterns Iterative techniques If it does not make business sense then it is not a good model! Segmentation in SPSS Techniques include: Factor Analysis / Principal Components Analysis Hierarchical Clustering K-Means Cluster Non-Linear Principal Components Analysis (PRINCALS/CATPCA) The new Two-Step Cluster Which Technique to Use? Which Test to use? Factor Analysis - to find patterns within variables Categories - use if data doesn’t fit assumptions for Factor Analysis Cluster Analysis - to find patterns between individuals Two-Step Cluster – To use with both categorical and continuous variables Discriminant Analysis - to look for differences between groups, try to predict target variable AnswerTree - combinations of data, to predict target Multivariate Analysis These techniques are inter-related, but don’t have to use all of them Can use a combination of these techniques to segment the data Main Considerations Looking for patterns or trying to make predictions? Levels of Measurement of the data (categorical or continuous) Sample size Missing values Does data fulfil assumptions for test?  Before you start……. ….. Check your data! Handling Missing Data Check before analysis for any patterns within missing data Check before analysis that missing val