Products for non-finacial institutions Data mining
Data
Mining
Data
mining is a method which allows to forecast a future status, trend or
behaviour of a client from the data gathered by a company, which it
often does not exploit (so called hidden data) and from additional
available resources. Based on such information, the company can adopt
a qualified decision about further steps that are more likely to be
successful.
The
first step of data mining is to define a need. Such need can concern
operations (need to decrease the cost of production, logistics...) or
marketing (need to increase sales, maintain key customers...). Such
defined need results in a specific analytical task. In case of
operations the task is e.g. to economise, in case of marketing e.g.
the identification what new products would customers be willing to
purchase and at what price or how to focus the marketing campaign.
An
important pre-requisite is the quality of data. Poor data lead to
unreliable information. That is why it is necessary to make
sufficient effort to search and clean data (Data Sourcing).
With
the application of analytical methods (usually decision trees or
neural networks) the company obtains precious information.
Data
mining is usually the domain of companies that have a sufficient
quantity of data and operate in a very competitive environment,
telecommunication
companies , department stores chains .
However, the method can be
very well used with many other companies, e.g. transport companies,
network of fuel filling stations, manufacturing
companies (utilization of data
of manufacturing machines) etc.
Telecommunications
Telecommunication
companies have a number of information about their clients (personal
characteristics of the client, history of used services, schedule of
utilization of services, payment discipline, etc.). The output of
data mining can be:
- proposal
of a package of services
- targeting of a
marketing campaign
- identification
the possibility that a client leaves
- identification of unusual behaviour (warning of a possible abuse of telephone)
Department stores chains
Department
store chains also have a number of data. If
such data are analyzed, it increases the likelihood that a correct
decision is adopted. Such data can be: frequency of purchases, amount
spent, purchased items, payment method. They are also instruments
(payment cards, customer cards) which allow to assign personal data
to individual purchases. Data mining can reveal information necessary
for:
- increasing
the loyalty of the client (to design a benefit program - discounts
for products often purchased by customers, special offers, gifts,
etc.)
- increasing
sales by obtaining new clients or through the increase of the sales
of selected items
- increasing sales through the establishment of strategic partnerships with other companies (identification of items often purchased together, identification of customer habits - dressing, spending of free time, etc.)
Manufacturing
companies
Databases
of manufacturing companies also contain data (data about the quantity
of consumption of direct or auxiliary material, duration of the
production cycle, etc.). The use of data
mining can reveal information necessary for:
- the
improvement of time synchronization of the production
- a better
utilization of the capacity of machines
(or production capacity in general)
- optimal production
batches, etc.
Advanced Risk Management a Data Mining
Since ARM's experts have mathematical and statistical education and practical experience, by combining the analysis of internal data with available statistical data they are capable to interpret the outputs of data mining with respect to macroeconomic and microeconomic environment.
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