abiba analytics

8/9/2019 ABIBA Analytics

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Abiba Systems | www.abibasystems.com

The Key To Drive Business Performance


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Analytics Solutions Overview

Churn Analytics Solution

Product & Technical Architecture

Deployment Model

Business Benefits

Roadmap

Pilot Project Status

Other Analytics Solutions


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Churn Prediction Predict the potential churn

individual subscriber and segment

level.

Perform survival analysis for existing

customers

Risk models

Identify the most risky customer

segments and list at-risk customers

Identify the customers who are

going to default or delay the payment

Response models

Identify the most sensitive customers

for cross selling/up selling

Identify customers likely to respond

to promotional offers

Segmentation and profilingIdentify your profitable segments and

their behavior

Estimate the life time value of your

customer segments for better

marketing


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ABIBA chartered a product based approach towards analytics due to followed benefits thataccrue to the customer

Low Total Cost of Ownership

Low Learning curve

Single vendor concept

Easy deployment

Embedded Best Practices

ABIBAs Analytics Suite comes as an integrated analytics product since it consists of the

following modules

Data Capture

Captures data from the various data repositories Data Integration - The data is integrated and converted to the required format.

Data Modeling Modeling is carried out and stored

Reporting & Analysis Module Reports are generated based on the models built.


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Common solution approach for different models.

Customise based on business requirements and data handled

Based on open architecture and component model.

Extracts required data from customer sources, transform and loadinto data marts.

Build models using historic data

Score the live customers for various predictions

Presentation tool for reporting and analysis

Analytics Solution Overview


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An effective churn solution should help operators do the following

1. Predict existing customer likely to churn

stop recharging

2. Predict suspended customers who are likely to recharge and come back

3. Predict the estimate future life of existing customers

Churn in scope

Postpaid and prepaid

Retail and Enterprise customers

Different products and services;

Regions and modes of Sales Channel

Churn prediction is done at

Segment level Churn prediction Customer level Churn prediction


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Solution should predict churn and satisfy the following major customer objectives

1. Accuracy

Accuracy of prediction of churn when compared with actual churns of

previous time period

Prediction Accuracy of 60% or above

2. Transparency Solution to identify the major drivers for churn

Identify the key drivers for the different customer segments covered in the

project

Present these drivers in a business user friendly interface

3. Configurability Configurability of solution parameters and objectives by the user team

To support the changing marketing requirements in achieving the retention

objectives of the operators



Solution Highlights

UI driven Modeling

Enhanced VisualizationScalable

Modeling Methodology

Proven modeling technique

Modeling Expertise of

ABIBA

Transparent modeling

methodology

Segment level modeling

using micro-models

Configurability

Business user driven

Modeling Build, Edit,

Maintain by Business Users

Managing Models - Project

and models

Reporting & Analysis

Deployment Mode

Quick Deployment

Consulting driven solution

End to End Solutions from

data processing modeling

deployment - support



Product Architecture

Customer

Segmentation

module

Response

modeling

module

Analytics Suite

Churn

Analytics

module

Data audit

& Analysis

Data Pre

processing

Modeling

& Scoring BI

Customer Intelligence Framework

Insights redefining objective and data

Data Sources

External files

Transaction

system

Business

Objective

Actionable Insights

Promotion

Retention

campaign

Product and

Pricing



Production Environment

Function Hardware

ETL Server 4* Quad Core processor

32 GB RAM, 500 GB Storage

Analysis(DB)

server4* Quad Core processor

32 GB RAM, 1 TB StorageApplication



Modeling



Development Environment

Function Hardware

ETL Server 4* Quad Core processor &


Analysis(D

B) server4* Quad Core processor &

32 GB RAM, 1 TB StorageApplicatio

n server1* Quad Core processor &


Modeling

server4* Quad Core processor &


Specifications for a subscriber base of 3 million

For deployment of upto 8 models



Production Environment

Function Software

ETL Server OS: Red Hat Enterprise Linux 5

Tools: Data Integration tool, Java

1.6

Analysis(DB)

server

OS: Red Hat Enterprise Linux 5

Tools: PostgreSQL 8.2,Champion

Application

server


Tools: Tomcat 6.x,Apache

2.2,Champion

Modelingserver


Tools:Modeler,Java 1.6

Development Environment

Function Software

ETL Server OS: Red Hat Enterprise Linux 5

Tools: Data Integration tool, Java

1.6

Analysis(DB)

server


Tools: PostgreSQL 8.2,Champion

Application

server


Tools: Tomcat 6.x,Apache

2.2,Champion

Modelingserver


Tools:Modeler,Java 1.6



Analytical Dashboard

Multi-dimensional Analytics

Trending Solution

Early Warning Solution

Key Business benefits

Our Analytics solutions help to

To identify postpaid customers most likely to churn

To identify prepaid customers who are likely to stop recharging

To identify suspended customers who are likely to recharge

To identify most Valuable Customers

To identify the likely response of customers to new marketing offers

To identify opportunities for up selling and cross selling of services

To identify postpaid customers more likely to default

The above predictions and analysis can be done at different segment levels

Product, region, Age on network, ARPU category etc..



Single Vendor One Stop shop No need for a 3rd party analytics tools and a

separate implementation partner.

Business user driven implementation No dependency on analysts, a scarce

resource in many markets

Embedded Best practices Technology and telecom domain

Ease of use Customisable GUI, workflow guiding model building

Integrated with other ABIBA solutions solutions like loyalty management,

convergent rating

Pre-built Telecom models reduced time to deploy

High level of configurability and customisation suits rapidly changingmarket dynamics

Off-shore driven deployment With data provided offshore

Lower overall TCO

Value Proposition



Churn Analytics Roadmap

March 2010

Column store database

Churn segment level profiling

User defined reports

GIS based Adhoc reports

Now

Churn Modeling

Integrated with database, ETL and

datamart

Integrated with BI solution

ETLDashboard

Canned analytics

Dashboards and

Reports



September 2010

Campaign management interface

Survival analytics

Recommendation engine

Rule based analytics

March 2011

ENTERPRISE INTELLIGENCE AND

DECISION MANAGEMENT


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