Cluster analysis has many uses. At its very basic level, a cluster is a group of people or objects that share similar characteristics. In the marketing and sales industries, clustering is important, since customers (or potential customers) can be grouped by characteristics such as average spending, frequency of purchase, and recency of purchases, and assigned a cluster that represents one single measure of the different levels contained in all of the attributes that make up that cluster. So, for our RFM example, cluster A might represent frequent purchasers who spend a lot of money, and spend often (every marketers dream). Cluster B could represent people who are just average consumers across all three of those RFM metrics, and there might even be a cluster Z which represents things that seem to be impossible, such as customers who buy Halloween costumes only...
Germany
Slovakia
Canada
Brazil
Singapore
Hungary
Philippines
Mexico
Thailand
Ukraine
Luxembourg
Estonia
Lithuania
Norway
Chile
United States
Great Britain
India
Spain
South Korea
Ecuador
Colombia
Taiwan
Switzerland
Indonesia
Cyprus
Denmark
Finland
Poland
Malta
Czechia
New Zealand
Austria
Turkey
France
Sweden
Italy
Egypt
Belgium
Portugal
Slovenia
Ireland
Romania
Greece
Argentina
Malaysia
South Africa
Netherlands
Bulgaria
Latvia
Australia
Japan
Russia