How to Run a Segmentation Analysis on SPSS


In marketing it is important to know your potential market. To get a sense for the existing market, you can perform a market segmentation, which breaks the market down into smaller groups that share common attributes. Knowing specific market segments will allow you to target these groups individually. Although the statistical methods of performing a market segmentation analysis are difficult, SPSS allows you to perform the analysis without knowledge of statistics.

  • Insert your data into the SPSS data editor. Each column should contain different demographic factors, such as age, income level or education. Each row should be a specific case, meaning another specific segment, such as gender or occupation.

  • Click "Analyze" in the menu bar then select "Classify" and then choose "Hierarchical Cluster."

  • Select the demographic variables you want to analyze from the screen where they should now be appearing by clicking each one and then pressing the arrow button to the right of the variables. These selections should then move into the box labelled "Variables" as you click the button.

  • Click the "Statistics" button to open a new dialog box. Select the number of cluster that you want to search for. You can either either select a specific number or allow the program to look within a range. Then click "Continue."

  • Click the button labeled "Method" and select "Ward's method" for the clustering method. Then press "Continue."

  • Click the button labelled "Plots" and check the box beside Dendogram." Then press "Continue."

  • Open the "Output" window in SPSS. This will now display the dendogram and highlight specific clusters. For example, if it found that here is a cluster of men aged 65 to 70 with an average income of $40,000 to $60,000, then it would highlight this cluster. These clusters represent specific market segments you can target.

Related Searches


  • "Data Mining Techniques in CRM: Inside Customer Segmentation"; Konstantinos Tsiptsis et al.; 2010
  • Photo Credit Sean Gallup/Getty Images News/Getty Images
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