SPSS, Direct Marketing, Chapter 3 and 9 Help Case Studies Direct Marketing Cluster Analysis File to be used: dmdata.sav See Chapter 23, SPSS Base Statistics for description of methods Metric/non-metric, large datasets, optimal clustering SPSS Multidimensional Scaling (Euclidean Distance)Ītlanta Chicago Denver Houston Los_Angeles Miami New_York San_Francisco Seattle Washington Measuring distances (two dimensions) D(b,a) A B Measuring distances (two dimensions) dac2 = (dx2 + dy2) A B Measuring distances (two dimensions, x and y) A B Measuring distances (differences) or proximities (similarities) between subjects Geo-Segmentation in CDA Birds of a feather f_k together… ī2B Segmentation Taxonomy Firm size (employees, sales) Industry (SIC, NAICS) Buying process Value within finished product Usage (Production/Maintenance) Order size and Frequency Expectations Product usage/loyalty Buying behaviour Preferred communication channel Family life cycle (stage in life) Lifestyle (personal values) Remember the basic marketing rules about segmentation (p.
Product usage, product attributes, communication, marketing channels Packages, prices, copy strategy, communication and sales channels Campaign Metrics and TestingĬlustering: Clustering and Segmentation B2C and B2B Clustering theory ĭifferences between clusters and segments Learning segmentation Dynamic segmentation ĭifferent needs and preferences Different responses to marketing efforts Where are we going from now? Reading week 7.
Data preparation and transformation Customer Classification 4. What is Business intelligence and database marketing 2. What have we seen so far? Data Architecture, CRISP and Preparation 1. MKT 700 Business Intelligence and Decision Models Week 6: Segmentation and Cluster Analysis
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