Book: Data Mining for Business Analytics in R

Hi

I am looking at Case 21.6 solution in R scripts.

21.6 Segmenting Consumers of Bath Soap6 BathSoap.csv is the dataset for this case study. Business Situation CRISA is an Asian market research agency that specializes in tracking consumer purchase behavior in consumer goods (both durable and nondurable). In one major research project, CRISA tracks numerous consumer product categories (e.g., "detergents"), and, within each category, perhaps dozens of brands. To track purchase behavior, CRISA constituted household panels in over 100 cities and towns in India, covering most of the Indian urban market. The households were carefully selected using stratified sampling to ensure a representative sample; a subset of 600 records is analyzed here. The strata were defined on the basis of socioeconomic status and the market (a collection of cities).

Assignment: 1. Use k-means clustering to identify clusters of households based on: a. The variables that describe purchase behavior (including brand loyalty) b. The variables that describe the basis for purchase c. The variables that describe both purchase behavior and basis of purchase Note 1: How should k be chosen? Think about how the clusters would be used. It is likely that the marketing efforts would support two to five different promotional approaches. Note 2: How should the percentages of total purchases comprised by various brands be treated? Isn't a customer who buys all brand A just as loyal as a customer who buys all brand B? What will be the effect on any distance measure of using the brand share variables as is? Consider using a single derived variable. 2. Select what you think is the best segmentation and comment on the characteristics (demographic, brand loyalty, and basis for purchase) of these clusters. (This information would be used to guide the development of advertising and promotional campaigns.) 3. Develop a model that classifies the data into these segments. Since this the information would most likely be used in targeting direct-mail promotions, it would be useful to select a market segment that would be defined as a success in the classification model.