Dimensions of Customer Segmentation

Discussion on customer segmentation invariably moves towards the variables or dimensions on which a segmentation exercise can be carried out. Words such as demographic, psychograpic, product purchase, transaction and interaction often pop up as possible dimension. And like the founder of a retail analytics product vendor, RFM is another definition of customer segmentation (see earlier post).

Today I attempt to list down the categories and dimension which could be input into a customer segmentation model. This list, though comprehensive, is in no way exhaustive. But I don't think this is an area of concern since not many companies could fill in a majority of these dimensions with customer data.

I have categorised the dimension into classes. For some dimension, I have also stated some sample values. I am not attempting to explain the dimension since a quick google on the meaning of the dimension name should give enough insight into its explanation and the likely values the dimension with contain in the data set.

1. Class: Geographic
 1.a: Region
 1.b: City size
 1.c: Density of area
 1.d: Climate
2. Class: Demographic
 2.a: Age
 2.b: Sex
 2.c: Marital status
 2.d: Income
 2.e: Education
 2.f: Occupation
3. Class: Psychological
 3.a: Needs-motivation
  sample values: shelter, safety, security, affection, sense of self worth
 3.b: Personality
  sample values: extroverts, novelty seeker, aggressives, low dogmatics
 3.c: Perception
  sample values: low-risk, moderate-risk, high-risk
 3.d: Learning involvement
 3.e: Attitudes
4. Class: Pscychographic
 4.a: Lifestyle
  sample values: economy-minded, couch potatoes, outdoor enthusiasts, status seekers
5. Class: Sociocultural
 5.a: Cultures
  sample values: Bangla, Egyptian, Indian, Nepali, Pakistani
 5.b: Religion
 5.c: Subcultures
  sample values: African, American, Asian, Hispanic
 5.d: Social Class
 5.e: Family life cycle
  sample values: bachelors, young married, full nesters, empty nesters
6. Class: Use related
 6.a: Usage rate
  sample values: heavy users, medium users, light users, non users
 6.b: Awareness status
  sample values: unaware, aware, interested, enthusiastic
 6.c: Brand loyalty
  sample values: none, some, strong
7. Class: Use situation
 7.a: Time
  sample values: leisure, work, rush, morning, night
 7.b: Objective
  sample values: personal, gift, snack, fun, achievement
 7.c: Location
  sample values: home, work, friend's home, in-store
 7.d: Person
  sample values: self, family members, friends, supervisor, manager, peers
8. Class: Benefit
 sample values: convenience, social accpetance, long lasting, economy, value-for-money
9. Class: Hybrid segmentation: implies using output of other segmentation model as an input to the current segmentation exercise.

Contact me at michaeldsilva@gmail.com if you want to discuss further on conducting a segmentation exercise for your customer base.