Graceful Growth Consulting (India) Private Limited · Attracting thousands of new subscribers is worthless if an equal number are leaving (MNP Issue) Minimizing customer churn provides

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Graceful Growth Consulting (India) Private Limited

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The Indian Telecom Industry

•3 Insight . Innovation . Agility

Draft National Telecom Policy - 2011

Opportunities

Increasing Mobile Subscribers

Untapped Rural Markets

Rising Internet Penetration

Development of Telecom Infrastructure

Growth in MVAS

Telecom Equipment Market

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Convergence, Consolidation & Competition

Today, numerous industry challenges are forcing

telecom companies to streamline operations and

increase competitive agility

The challenges include:

Tariff war, Lower ARPU and multiple operators in each circle resulting in profit decline

Demanding and volatile users, Multiple SIMS, shift from Customer Market Share to Revenue Market Share (RMS)

Convergence of Service, 3G and BWA Rollout

Industry Consolidation

Increased competition and diminishing revenue streams

Rural Penetration

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Can Soft-Computing Techniques help Managing these Challenges?

Insight . Innovation . Agility

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Churn Management – A bottom line Issue

Attracting thousands of new subscribers is worthless if an equal number are leaving (MNP Issue)

Minimizing customer churn provides a number of benefits, such as:

Minor investment in acquiring a new customer

Higher efficiency in network usage

Increase of added-value sales to long term customers

Decrease of expenditure on help desk

Decrease of exposure to frauds and bad debts

Higher confidence of investors


First Thing First

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Churn can be defined and measured in different ways:

“Absolute” Churn. number of subscribers disconnected, as a percentage of the subscriber base over a given period

“Line” or “Service” Churn. number of lines or services disconnected, as a percentage of the total amount of lines or services subscribed by the customers

“Primary Churn”. number of defections

“Secondary Churn”. drop in traffic volume, with respect to different typology of calls


Churn Management – What it means?

Measuring churn is getting more and more difficult

Growing tendency for Business users to split their business between several competing fixed network operators

Carrier selection enables Residential customers to make different kind of calls with different operators

Carrier pre-selection and Unbundling of the Local Loop makes it very difficult to profile customers according to their “telecommunication needs”

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Developing a Churn Analysis system based upon data mining technology to analyze the customer database

and predict churn


Example: Predict churn/no churn situation of any

particular customer given 5 months of historical data


•21 millions of residential customers

•23 millions of customers

•2 millions of business customers

•Usage patterns analysis

of Voice Services by

single subscriber line


of Voice Services by

subscriber line, contract,

company, etc.


of VAS by single

subscriber line

Solution Scope (Case Study)


Application Framework


Data Understanding

Customer

Data Warehouse

Input Data

Customer demographics

Basic customer information

Service Profile

Products/services purchased by

each customer.

Tariff plans

Details of the tariff scheme in

use

Extra service information

Special plans / rates

Service bundles

Call data aggregated by month

Billing data aggregated by

month

Complaint information

Fraud and bad debts data

Customer service contacts

Sales force contacts

Market data

13 operational systems (Sample Case)

(Subscriber Data in Multiple Systems)

More than 500 indicators per customer

Extraction delay: 2 months

Loading: on a monthly basis

Size: 1.5 Tb

Subscriber Data Management in 4G Network


Keep More of Your Revenue Plug the leaks as they are discovered

The ability to predict where the new revenue leaks

may occur is the biggest opportunity for the bottom

line improvement

This means to perform in-depth revenue assurance

analysis on a billion or more transaction a day !

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Capturing more of the money earned from booked and delivered services is the best strategy for growth in the maturing markets such as mobile telephony and broadband Internet

Without the state-of-the-art revenue assurance solution, the endemically leaky situation (disparate networks, legacy systems, inconsistent data sets, policies and procedures that may have been resulted through M&A) can slow ROI


Revenue Assurance as Growth Strategy

The network facing systems cause majority of the leaks

The focus, therefore, should be on switch-mediate-rating/billing processes

Solution providers address both customer facing and network facing systems


Advanced analytics, such as profile-driven neural networks, look at non-linear interrelationships between thousands of data points at a time

Powerful pattern recognition capabilities enable them to recognize subtle, hidden and emerging patterns of revenue leakages across the network

Software based, automated, real-time analysis


Revenue Leakage in Hand-off


Predicting and Eliminating Leakage Before it Happens

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Next Generation Revenue Assurance Solutions are based on advanced analytics, such as analytic profiles and neural network models, to monitor the operations for revenue leakage and leakage risk

The new models are trained on actual data to spot the data-driven variable patterns associated with revenue leakage

Neural network based solutions detect more revenue leakage because they see more of what’s going on in the network

State-of-the art systems bring a vast amount of historical data to bear on real-time transactions through the use of ‘dynamic profiles’


Next Generation Revenue Assurance Systems


Marketing Analytics for Effective Campaign

Management

As an Example, is 3G adoption a Campaign issue?


Marketing analytics

Marketing analytics is extremely a customer-centric process and it primarily

utilizes the statistical and the advanced mathematical techniques for predicting

the future behavioral characteristics and the product or the service preferences of the customers based on the historical information

The Marketing Analytics helps to:

Understand the customers

Identify customer segments and also approaching with new effective strategies for business

Identify the key markets

Manage the competitors , satisfaction and demands of the stake holders and ROI in business

Identify avenues to create business value

Analyze the data in the areas like

Customer Tenure

Customer interaction (demographic, behavioral, attitudinal

Customer net present value

Customer Preference

http://www.marketbright.com/products/marketing-analytics.html


Marketing analytics (Case study)

The data from the agencies like ABI, DNB

And the Internal customer data is used as source (14 M Records)

The data is cleansed and parsed to get all the data into standard

format using Trillium so that the further processing is simpler

Business names and addresses (site) are grouped based on

the location

Assignment of House Hold Ids to business and site

The grouping is done further into customers and prospects

The revenue roll-up for the logical groups business and site

High Level Process Flow:

The various process in the process flow are applied with well defined business

rules based on the requirements of the business user

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Finally – Have your bills right !

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Conclusions

According to the Science of Soul..

When in ‘Samshaya’ (Doubt or State of Indecision)..

A normal (Analytical) logic invariable takes us to ‘Viparyaya’ (Mistaken View, Incorrect Decision

against the real nature of things)

It is only through the experience, judgment (Inductive Reasoning / Fuzzy logic) helps us to

tilt towards the ‘Dharana’ (Decision)

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Thank You


For Queries Contact

[email protected]

Phone: +91 97644 49718

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Graceful Growth Consulting (India) Private Limited · Attracting thousands of new subscribers is worthless if an equal number are leaving (MNP Issue) Minimizing customer churn provides