Download The data mining process and SAS Enterprise Miner in Elisa

The data mining process and
SAS Enterprise Miner
in Elisa Communications Corporation
Jaana Järveläinen
SeUGI 19, Florence May 29-June 1 2001
Elisa Communications Corporation
International
Customer-oriented
Communications service provider
What is Elisa?
Mission
Elisa offers its customers communicationsbased services, experiences, information
irrespective of time, place and means.
What does Elisa do?
Elisa’s Market Areas
• Principal market area is Finland
• From metropolitan expert to
strong nationwide operator
• International activities
• in Germany
• in the Baltics
• globally - through
selected products
Where does Elisa operate?
Objective
• In 2005, Elisa is the leading provider of total
communications-based services in Finland.
• In the Baltic Rim, Elisa has profitable and
progressive business units in selected product
and customer segments.
• At the global level, the Group is strong in
selected business areas.
Success is Achieved
• By developing long-term customerships
• By integrating technology and services
• By focusing on the reliability of services
and operations
Elisa Group’s Business
MOBILE
* Radiolinja Oy
* Radiolinja Eesti AS
GERMAN OPERATIONS
* Elisa Kommunikation GmbH
* City Carriers
* Mobile distribution
(Mäkitorppa)
* Long-distance and
international voice
services
FIXED NETWORK
* Elisa Communications Corporation,
parent company
* Datatie Oy
* FINNETCom Oy
OTHERS
* Comptel Plc
* Mäkitorppa Yhtiöt Oy
* Kolumbus Oy
* Direktia Ltd
* Heltel Oy
* Epstar Oy
Meeting the Clients’ Needs
• Development of business and services into
customized solutions
• Creation of total solutions together with customers
• Active, responsible customer care
• Comprehensive, nationwide distribution network
Value - customer orientation
Continuous Progress
Business expansion and rapid technological
changes create a platform for:
• individual and team-based learning;
upgrading of professional expertise
• utilizing expertise gained in Finland
in international operations.
• special focus on developing the quality of
customer relations
Value - responsibility
Enhanced Technology, Products and
Services
• Commoditized products per customer segment
• Advanced technological applications, e.g.
• mobile location services, electronic
authentication systems, telematics applications
• Upgradal of networks for future needs
• broadband, web- and IP-based
networking
• Extensive strategic R&D cooperation, in Finland
and abroad
Value - pioneering spirit
Solid Business
• Profitable customer relations ensure continuity of
operations
• Flexible, fast reacting to market changes through
updateable product and service portfolio
• Synergy from intra-group cooperation facilitates
enhanced operations
• Cost-effective operations
Value - profitability
Data mining process,
background
• Personal Communications -SBA test used the
Enteprise Miner during the last August - September,
2000
• The idea was to find out more about Elisa’s customers
and why they choose to give up their contracts and
telephone subscriptions
What did we do?
• We tried to predict these cases as exactly as possible
• We tried to slice and dice the customer segment to find
out the churn (who were those to give up our services
in the consumer section)
• We wanted to see if the tool (Enteprise Miner ) was
applicable to our current technology architecture and
also if the mining itself shold be applicable to Elisa’s
DW strategy
How did we do it?
• Part one: Created a mathematical model using data
mining methods to predict our customers - not natural
churn
• Part two: The churn was modeled so that every home
customer was generated with the created model and
the probability cause was that the client would stay as
our customer in the future, too
• Part three: use the SAS script for new data
What did we learn about the tool?
• Enteprise Miner tool supported the open access and
management to third party databases (e.g. oracle, db2)
and we could use our existing databases as sources
• It is expensive and needs more resources (analysts
and IT people)
• It is a progressive and versatile product
• It could add our ability to analyze the existing data and
information in our operative systems
• It could also be used in our CRM process
… or from the process itself?
• As we think that quality through effective customer
management is important key to successful customer
service, we need to build the same quality in our data
warehousing and data mining processes.
• To avoid pitfalls of the mining process (as we had not
done it before), we used experienced consultant and
the leading tool in the data mining market area – that is
Enteprise Miner -tool.
Key elements in succesful DM project:
• business knowledge from the business analysts
• a clear case of where to try the mining process
• the central IT resources must be available
• the links to our existing data warehouses and other
data sources must be available
• knowledge in statistics and of the tool itself (in our
company or as we did: a consultant)
• data definitions were made and handled in business
terms
• business people were enthusiastic
The future vision:
• We will use the data mining in our marketing, in
analysing network transaction and in click-stream
analysis in order to follow the development of our
customer base and try to observe the early signs if
anything strange happens in our markets
Conclusions:
• Even though data warehousing and data mining
architecture and tools are expensive to install and
maintain, some investments are required to ensure that
the right information and knowledge at the right time
are delivered to our business management. We need
tools to know our customers better and to serve them
in any situations. The mining offers tool to predict and
analyze our existing customer base.
Thank you!
Any questions?
[email protected]