Download Churn Prediction - The important element in the retention process

Mag. Gerhard Wanek
Churnprediction
The important element
in the retentionprocess!
mobilkom
kom austria
mobilkom austria intern
1
Churnprediction
Mag. Gerhard Wanek
Content
•
•
•
•
•
•
•
•
•
mobilkom and the market
The understanding of “churnprediction”
Retention process and interaction
The process of churnprediction
IT architecture and datamining
Juicing the right tool - but how?
The right model to predict churn
Marketing action - contacting the customer
Critical success factors
mobilkom austria intern
2
Churnprediction
Mag. Gerhard Wanek
mobilkom
kom and the market
• mobilkom is a stock corporation ownd by
Austrian telekom and telecom italia
• the leading company in the austrian market
(3 competitors)
• 97 % coverage of the population
• 55 % marketpenetration
• 52 % marketshare
• 2,5 million customers (GSM + TACS)
• 1.800 employees, 800 in customer services,
100 in customer retention
• 20.000 - 25.000 service calls per day
mobilkom austria intern
3
Churnprediction
Mag. Gerhard Wanek
The understanding of “churnprediction”
• analyse existing customer data with a
datamining-tool (SAS Enterprise Miner)
• predict customers with a high risk to churn
and with high value for the company
• proactive contact of the predicted customer with the
goal to retain them
• designing retention offers to optimise the
customer lifetime value
mobilkom austria intern
4
Churnprediction
Mag. Gerhard Wanek
Retention process and interaction 1
Retention Process
Customer Lifetime Cycle
Welcome Calls
Loyaltyprogram
First Bill Calls
Churnprediction
Thank you Calls
mobilkom austria intern
Winback
Save
Cancellation
Churn Call
5
Churnprediction
Mag. Gerhard Wanek
Retention process and interaction 2
Retention Process
• Welcome calls
• First bill call
• Thank you call
•
•
•
•
•
Churnprediction
Save
Winback
Cancellation
Churn calls
mobilkom austria intern
start up a relation
confirm the relation
use the chances for
cross selling
one step ahead
retain customer
for high value customer
be fair and polite
analyse the churn
behaviour
6
Churnprediction
Mag. Gerhard Wanek
Retention process and interaction 3
Marketing
Sales
IT/DWH
Call Center
Finance
Churn
Prediction
Customer
mobilkom austria intern
7
Churnprediction
Process of churnprediction 1
Mag. Gerhard Wanek
Project steps
Examples
Definition of the required
variables for the predicting
model
Demographic data,
development of the CDR´s,
information about the contract
Extraction of the data from
the IT Systems, Set-up of
the Datamart
Evaluation of the data sources,
data quantity and quality, setup and loading of the datamart
Building up of the statistic
models to predict possible
churning customers
Customer A with a value of X
will churn in July with a
probability of 90 %
Interpretation of the
churnprediction results and
conclusions
Possible indicators of churn:
duration of the contract, call to
other networks ...
Design and realisation of
Retention campaigns
Hardware replacement, special
services ...
mobilkom austria intern
8
Churnprediction
Mag. Gerhard Wanek
Process of churnprediction 2
• goal definition - define a clear and precise goal
• data sources - cheque carefully all you internal and
external data sources
• data quantity - cheque carefully which data do you
need to reach the goal = business case
• data quality - how good are the dates you have now is a good opportunity to clean the data further questions of datamining will follow
• modelling - you need both statistic know how and
know how of your business
• marketing campaigns - churnprediction does not end
with a perfect model you have to
convince the churning customer!
mobilkom austria intern
9
Churnprediction
Mag. Gerhard Wanek
IT architecture and datamining 1
external
Data
DataDatawarehouse
Internal
Data
DataMart
Data Mining
Environment
Model-Code
Reporting
ProductionApplication
Model
Score-Daten
mobilkom austria intern
10
Churnprediction
Mag. Gerhard Wanek
IT architecture and datamining 2
Data Mining with SAS Enterprise Miner
SEMMA-Methode
Sample Explore Modify
Model
Assess
Copyright 1998 by SAS Institute Inc., Cary, NC
mobilkom austria intern
11
Churnprediction
Mag. Gerhard Wanek
Juicing the right tool - but how?
• collection of all the requirements
• create a list of assessment- and knock outcriteria's
• checking of the solutions/tools
• shortlist of 3 solutions
• visit to reference-customers to see the solutions
in production
• test case
Decision for:
mobilkom austria intern
the most flexible tool
with local datamining support
in combination with a
consulting/marketing support!
12
Churnprediction
Mag. Gerhard Wanek
Marketing action - contacting the customer
• increase the customer lifetime value
• increase the loyalty of a single customer/segment
Customer Loyalty Program:
- Mobilcircle
- Mobilpoints
Hardware Replacment:
- A1 Next
Individual retention offers!
• feedback loop - learning from the experience of the
first marketing activities in the churnprediction
project
mobilkom austria intern
13
Churnprediction
Mag. Gerhard Wanek
Critical success factors
•
•
•
•
clear definition of your goal
clear and well structured project plan
good data quality
a proven quality of the co-operation of the
involved parties (marketing, IT, CC ...)
• the understanding of a solution step by step
• the link between the project and the operative life
bring it to the customer!
• you need a project sponsor at the right
organisational level
mobilkom austria intern
14
Churnprediction
Mag. Gerhard Wanek
Thank you very much and
enjoy the
mobilkom austria intern
15