Customer Segmentation Through K-Means and Hierarchical Clustering Techniques |
Author(s): |
| Prasanna Balaji , Great Lakes Institute of Management; Anika Singh, Great Lakes Institute of Management |
Keywords: |
| Clustering Techniques, Customer Segmentation through K-Means and Hierarchical Clustering Techniques |
Abstract |
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Clustering techniques are used to group data/observations in a few segments so that data within any segment are similar while data across segments are not similar. Defining what similar and different observations mean is an important part of cluster analysis which often requires a lot of contextual knowledge and creativity beyond what statistical tools can provide. Based on how we define similarities and differences between data observations like customers or assets, which can also be defined mathematically using distance metrics, one can find different segmentation solutions. |
Other Details |
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Paper ID: IJSRDV5I70298 Published in: Volume : 5, Issue : 7 Publication Date: 01/10/2017 Page(s): 512-516 |
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