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Data Mining BS/MS Project Clustering for Market Segmentation Presentation by Mike Calder Clustering • Used for market segmentation – Researchers want to find groups that can be targeted with the same marketing strategy • Given data of which users click on certain adds, derive discriminative clusters Strategy seen in use for almost 2 decades! 2 Motivation • Marketing companies want to produce as few ads as possible while tailoring to the largest possible audiences • Search engines already collect enough statistics to make these derivations – No extra methods needed to obtain data 3 Sample Click Data from Yahoo! Taken from (Haider, 2012) Represents the volume of advertisement clicks on Yahoo! (different colors indicate categories) 4 How Can We Use The Data? • Sample Data Attributes – Time advertisement was clicked on – Location of the click on the page – Category the advertisement falls into – Type of marketing strategy used in the ad • Must decide on a clustering algorithm and a number of clusters to use 5 Clustering Method Options • Algorithms – K-means – Hierarchal – Centroid-based – Distribution-based – Novel combinations of the above • Attempting to maximize “log-likelihood”. 6 Sample Algorithm Testing Taken from (Haider, 2012) Novel algorithm details are described in Discriminative Clustering for Market Segmentation 7 References • P. Haider. “Discriminative Clustering for Market Segmentation”. in Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD ’12). New York, NY, USA: ACM, pp. 417–425. 2012. • S. Dolnicar. “Using cluster analysis for market segmentation”. Australian Journal of Market Research, 11(2), 5-12. 2003. • F. Pratter. “Clustering for Market Segmentation”. Abt Associates Inc.. 1997. 8