Geo-Demographic Segmentation System
Kudos is now able to provide Clients with a Geo-Demographic Segmentation system at a much lower cost to those from other companies!SONAR is a truly unique segmentation system that divides the population of Great Britain into 80 mutually exclusive groups according to the types of neighbourhood in which they live. To do this a number of different data sources were used and these include:- 2011 Census data- Postcode classification of Wealth- Postcode classification of Consumer Activity- Land Registry data on house prices and sales activity- Council Tax BandsThese sources were carefully examined and key variables that would provide maximum discrimination were chosen to build the classification. A number of different statistical techniques were tested and a huge number of different cluster solutions were built and compared before the final preferred solution was chosen. SONAR is the final result of our Geo-Demographic Segmentation.The 80 SONAR codes are organized into 6 broad lifestage groups, which are•Group A – Young Singles•Group B – Young Families•Group C – Families•Group D – Mature Families•Group E – Empty Nesters•Group F – RetiredThis is the first character of the three character SONAR code. They are also organized into 4 quartiles representing wealth:•Group 1 – Affluent•Group 2 – Comfortable•Group 3 – Less Comfortable•Group 4 - StrugglingThis is the second character of the three character SONAR code.Thus, from the first two characters it is possible to identify the lifestage group and the wealth quartile. As an example, in the SONAR code A11 – “Metropolitan Young Professionals”. The A represents ‘Young Singles’, and the second digit the wealth quartile 1 the most affluent 25% of the country. Another example would be, SONAR code F44 – “Elderly Struggling Council Tenants” where F represents the elderly lifestage and the first 4 showing the least affluent 25%.
Contact Us!
Contact Kudos for more details on our Geo-Demographic Segmentation: info@kudos-data.com or telephone 0330 043 1583