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Statistics

Statistics
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Statistics


It is the duty of the business organization to adopt productive tools and methods for managing
the competition. Most of the international business organizations are using multivariate statistics
in order for understanding the customer trends and preferences. According to the words of Lisa
Dorward (200) multivariate techniques are highly useful for the business organization to identify
the new market opportunities and trends. We know the fact that the main objective of the
usiness organizations to gain profit, in order for attaining this objective the organization has to
introduce productive techniques and strategies. Now we can analyze the importance of
multivariate techniques in business in a detailed way.
Cluster Analysis and Business strategy
While compared other multivariate techniques such as factor analysis and multivariate
dimensional scale we can understand that cluster analysis is highly helps for starting new
usiness and providing productive services to the customers. Most of the companies in world are
using cluster analysis for classifying their customer and segments. Cluster analysis called as the
major application in business analytics and helps for grouping the similar data or objects in a
productive way (Cradit et al 2017,p.300). By using cluster analysis we can able to identify the
association different objects and data. For our company we can use different types of clustering
analysis for managing the resources, people and technology in a effective way.
Types of clustering variables used in business
General or specific
General clustering variables includes, different internal and factors that affects the business
process and activities. In the specific clustering variables it is only includes the aspects related
with the product or services. With the help of general or specific clustering variables the business
Statistics


organization can easily identify the controllable and uncontrollable factors the influence the
usiness strategies and process.
Observable or unobservable
Observable clustering variables are easy to measure and identify, in the case of unobservable
clustering variables we have to face some difficulties.
General Specific
Observable clustering
variables
 Cultural
 Demographic
 Geographic
 Technological
 Socio-economic
 Brand loyalty
 Store loyalty
 User status
 Usage
frequency
Unobservable
clustering variables
 Values
 Beliefs
 Customers
 Personality
 Attitude
 Perception
 Intention
 Preferences
Source: fo
es.com
The organization can consider these variables when they focus on new business or the segments.
We know the fact that most of business organization are trying to achieve the sustainable
competitive advantage. In order for attaining these objectives the organizations have to analysis
customer segments and introduce innovative products (Gilron et al 2017, p.113). With the help
of clustering analysis they can able to understand the needs of the customers. It also...