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AAUM Confidential

Analytics for

Telecom

Corporate profile

Founded by IIT Madras alumnus having extensive global business experience with Fortune 100 companies in United

States and India having three lines of business

Prof Prakash Sai

Dr. Prakash Sai is professor at the Department of Management Studies, Indian Institute of Technology Madras. He has wealth of international consulting experience in Strategy Formulation

Puneet Gupta

Puneet spearheads the IFMR Mezzanine Finance (Mezz Co.), is strengthening the delivery of financial services to rural households and urban poor by making investments in local financial institutions.

Padma Shri Dr. Ashok Jhunjhunwala

Dr. Ashok Jhunjhunwala is Professor at the Department of Electrical Engineering, Indian Institute of Technology Madras India. He holds a B.Tech degree from IIT, Kanpur, and M.S. and Ph.D degrees from the University of Maine, USA.

Analytics

• Appropriate statistical models

through which clients can measure

and grow their business.

Competitive Intelligence

• Actionable insights to clients for

their business excellence

Livelihood

•Services ranging from promotion of

livelihoods, implementation services,

livelihood & feasibility studies.

Key Focus Areas in Advanced analytics and Predictive analytics

Product – geniSIGHTS (Analytics/BI), Ordo-ab-Chao (Social Media)

More than 25 consulting assignments for Businesses & Govt orgs

Partnership – Actuate, IIT Madras, TIE and 3 strategic partnerships

Dedicated corporate office at IIT Madras Research park since 2009

Aaum’s office, IIT Madras Research Park

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Competencies in

Advanced analytics

Build appropriate statistical models through

which clients can measure and grow their

business.

Expertise in

• Digital Media

• Finance/Insurance

• Travel & Logistics

• Retail

• Entertainment

• Human Capital

• Government organizations

• Research & training

Competitive

assessment

Competitive intelligence

Provide actionable insights to clients for

their business excellence.

Expertise in

• Business Entry

• Business Expansion

• Market research

Livelihood

Perform livelihood services ranging from

promotion of livelihoods, implementation

services, livelihood and feasibility studies.

Expertise in

• Government organizations

• Non Government organizations

• Corporate with livelihood focus

• Research

- 4 -

Relevant Solutions

for

Telecom

Analytical Advantage Using Mathematical modeling

- 5 -

AAUM’s capability in analytics stems from expertise to extract insights from data sources with the

ability to develop advanced mathematical models aided by experience in using statistical tools

Data sources

Business

Rules

formulation

Analytical

model development

Analytical Advantage Using Mathematical modeling

Secondary

research

Client Primary

research Census

Research

firms

Statistical Tools

R (Statistical

System)

WEKA (Machine

learning software)

SPSS (Multivariate

Statistical Analysis)

SAS (Data mining,

Statistical, and

Econometric

modeling)

Analytical Advantage

Profiling &

Segmentation

Product

/Process

performance

Product

/process

innovation

Valuation,

Loyalty & life

time

Market Intelligence | Finance | Retail | Telecom | Supply Chain | Consulting

Client

- 6 -

Our Telecom services include

Complaints Analytics

Segmentation Demand

Forecasting

Collection analytics

Performance Analytics

Pricing Analytics Cross and Up

Selling

Churn Analytics

Telecom offerings

- 7 -

Churn analytics

Methodologies :

Logistic regression

Lift Curve

Data required:

Customer database for past few years.

The data could consist only of personal customer information.

Click for Demo

- 8 -

Click for

Cross selling / up selling

Methodologies:

Cross/Up Sell Model Data mart

Market basket analysis predictive

model.

Data required:

• Customer, Contract, Account, Services,

Plan data

• Call detail records (CDR‟s) for pre-paid

and post-paid customers

• Disconnection, Credit, Payment

information (current and historical)

Demo

- 9 -

Pricing Analytics

Methodologies:

Price plan performance analytics

Rate Plan vs. Revenue Impact analytics.

Data required:

Price of all the products vs competitors

price data

Demo Click for

- 10 -

Complaints Analytics

Methodologies:

Segregating the complaints data on a common

taxonomy, based on a standard lexicon of definitions

of terminology and types of complaints.

Qualifying the data by severity of problem,

periodicity of occurrence, type of fault detected, etc

Statistical analysis across parameters and derive

intelligent insights from the data either as predictive

models, or as behaviour model or segment the data

into intelligent patterns

The algorithm identifies new issues in the field and

flags higher-than-normal rate faults and notifies the

appropriate analyst to let them know there is a

problem that needs investigating.

Data required:

Customer care complaints database.

Complaints on the products.

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Text mining for call logs data – Frequency , similarity, clustering,

association rules to reveal text patterns

Frequently occurring terms are sent, helpdesk, etc.

Frequent terms used in the database

Clustering of call logs on the bag of

words used

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Text mining for call logs data – Lexicon based approach and advanced

machine learning algorithms for sentiment mining

Lexicon based commentometer to qualify the positivity and negativity in choice of words

negative neutral

negative 4 0

neutral 6 30

True clustering of the comments – SVM method

Algorithm driven clustering of the comments

Accuracy level of 85% from SVM method.

Advanced analytical

algorithms for sentiment mining

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Performance analytics

Methodologies

In order to better analyze the

performance, one needs to ensure

following steps are followed.

Gathering data

Analyzing data

Presenting information in a meaningful

way

Data required:

Sales ratio data

Demo Click for

- 14 -

Segmentation analytics

Methodologies:

Customer Segmentation for Trend Monitoring

and Forecasting

Customer segmentation using decision tree

Marketing Response Analysis with Gains & Profit

Charts

Data required:

Geographic variables

Psychographic segmentation variables

Behavioral segmentation variables

Past business history, Customers' past business

track records

Demo Click for

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Collection analytics

Methodology:

Market basket analysis

Data required:

Customer, Contract, Account, Services, Plan

data

Call detail records (CDR‟s) for pre-paid and

post-paid customers

Demo Click for

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Demand forecasting

Methodologies:

Methods that rely on qualitative

assessment

Methods that rely on quantitative data

Data required:

Call detail records (CDR‟s) for pre-paid

and post-paid customers

Disconnection, Credit, Payment

information (current and historical)

Demo Click for

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Questions/Feedback?

Contact us

01 N, 1st floor IIT Madras Research Park, Kanagam road, Chennai – 600113

Tel :` +91 44 66469877, Fax:+91 44 66469877

Email: info@aaumanalytics.com, Skype:b.rajeshkumar

Twitter: AaumAnalytics, Web: www.aaumanalytics.com

Facebook: http://www.facebook.com/AaumAnalytics

LinkedIn: http://www.linkedin.com/company/aaum-research-and-analytics-iit-madras

About Aaum

Aaum Research and Analytics founded by IIT Madras alumnus brings in extensive global business

experience working with Fortune 100 companies in North America and Asia Pacific. Incubated at IIT

Madras Incubator ecosystem with a focus on researching and devising the sophisticated analytical

techniques to solve the pressing business needs of corporations ranging from Health Care,

Entertainment, FMCGs, finance, insurance, retail, Telecom.

Aaum’s office at IIT Madras Research Park