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PRESENTATION ON CLUSTER ANALYSIS Marketing Research Methods Presented by:
Cluster analysis  ,[object Object],[object Object],[object Object]
Cluster Analysis ,[object Object]
Cluster Analysis and marketing research ,[object Object],[object Object],[object Object],[object Object]
Steps to conduct a Cluster Analysis ,[object Object],[object Object],[object Object],[object Object]
 
Defining distance: the Euclidean distance ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Clustering procedures ,[object Object],[object Object],[object Object],[object Object],[object Object]
Agglomerative clustering
Agglomerative clustering ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
K-means clustering ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Hierarchical vs Non hierarchical methods ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Suggested approach ,[object Object],[object Object]
Defining the number of clusters: elbow rule (1) n
Elbow rule (2): the scree diagram
Validating the analysis ,[object Object],[object Object],[object Object]
SPSS Example
 
Number of clusters: 10 – 6 = 4
 
Open the dataset supermarkets.sav ,[object Object],[object Object],[object Object]
The supermarkets.sav dataset
Run Principal Components Analysis and save scores ,[object Object],[object Object],[object Object]
Cluster analysis: basic steps ,[object Object],[object Object],[object Object],[object Object]
Analyse / Classify
Select the component scores Select from here Untick this
Select Ward’s algorithm Click here first Select method here
Output: Agglomeration schedule
Number of clusters Identify the step where the “distance coefficients” makes a bigger jump
The scree diagram (Excel needed)
Number of clusters ,[object Object],[object Object],[object Object],[object Object]
Now repeat the analysis ,[object Object],[object Object],[object Object],[object Object]
K-means
K-means dialog box Specify number of clusters
Save cluster membership Click here first Thick here
Final output
Cluster membership
Component meaning (tutorial week 5) 1. “Old Rich Big Spender” 3. Vegetarian TV lover 4. Organic radio listener 2. Family shopper 5. Vegetarian TV and web hater
 
Cluster interpretation through mean component values ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Which cluster to target? ,[object Object],[object Object],[object Object]
Representation of factors 1 and 4 (and cluster membership)

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Cluster spss week7