Difference between revisions 12269095 and 13366937 on enwiki

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Cluster analysis (in marketing)
'''Cluster analysis''' is a class of [[statistics|statistical]] techniques that can be applied to data that exhibits &#8220;natural&#8221; groupings. Cluster analysis sorts through the raw data and groups them into clusters. A '''cluster''' is a group of relatively homogeneous cases or observations. Objects in a cluster are similar to each other. They are also dissimilar to objects outside the cluster, particularly objects in other clusters(contracted; show full)
*Selecting test markets (see : [[experimental techniques]])<BR>

==The basic procedure is:==
# Formulate the problem - select the variables that you wish to apply the clustering technique to
# Select a distance measure - various ways of computing distance:
#*Squared Euclidean distance - the square root of the sum of the squared differences in value for each variable
#*Manhattan distance - the sum of the absolute differences in value for any variable
#*
[[Pafnuty Chebyshev|Chebychev]] distance - the maximum absolute difference in values for any variable
# Select a clustering procedure (see below)
# Decide on the number of clusters
# Map and interpret clusters - draw conclusions - illustrative techniques like [[perceptual mapping|perceptual maps]], icicle plots, and dendrograms are useful
# Assess [[reliability (psychometric)|reliability]] and [[validity (psychometric)|validity]] - various methods:
#*repeat analysis but use different distance measure
(contracted; show full)


''See also : [[marketing]], [[marketing research]], [[factor analysis]], [[multi dimensional scaling (in marketing)|multi dimensional scaling]], [[quantitative marketing research]], [[positioning (marketing)|positioning]], [[perceptual mapping]]''

[[Category:Psychometrics]]
[[Category:Marketing]]
[[Category:Marketing research]]
[[category:Product management]]