© 2014 – PROPRIETARY AND CONFIDENTIAL INFORMATION OF CVIDYA April 21st , 2015

Your Success is Our Business

Big Data Monetization The Path from

Internal to External

Hezi Zelevski VP Corporate Development hezi.zelevski@cvidya.com

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Everybody is Talking about Big Data…

“Top Technology Trends Impacting Information Infrastructure in 2013”

However…

“Processing large volumes or wide varieties of data, remains merely a technological solution, unless it is tied to

business goals and objectives ”

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Reduce operational costs Increase revenues, launch

Decline in traditional service revenues (Voice, SMS)

Unlimited Price Plans

Increasing competition Consolidations & mergers Global financial recession

Real-time Self-Service Data

Monetization

New services /products: “ Internet of Things ”

Data Explosion

New Billing Schemes

Telecom Market Trends

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Data Monetization Opportunities

Internal

− Effective customer proposition

− Effective campaigns execution

− Greater value and differentiation versus

− ……

External

− Resell aggregated data to third party partners in the form of trends

− Profiles

− Location

− usage patterns

− Movement

− ......

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External Monetization is Still at Early Maturity Stages

60% of operators believe that “it is important for Telcos to harness the power of Big Data to drive new revenue streams externally...”

Only 10% of respondents claimed they are currently focusing on an external monetization program for their subscriber Big Data

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External Monetization - Push or Pull ?

End Subscriber Added value

Third Party Use cases Customer engagement

Operator Data Platform

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Accelerating Business Breakthroughs

The right Use Cases

Location

Advertisement

Financial

…….

External Monetization Bid Data Solution

External web portal

Rich GUI with analytical and

reporting capabilities

Control over the data

3rd Party Engagement

3rd party value

Partnership

Market knowledge

Privacy &

Regulation

Customer data

Complete

Accurate

Enriched

Online

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Big Data Analytics Platform

Data Analytics

Use Cases

Big Data

The Analytics Workflow

Big Data CRM Usage DPI Location ERP DWH Billing Switch …….

Data Analytics

Collection Verification Enrichment Aggregation

Use Cases

Value Solution Analysis Simulation Action Monitoring

Big Data Analytics Platform

Use Case Example

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Examples for External Monetization Use Cases

Targeted Advertising Micro-segment the base into behavioral, demographic and geographic segments, offering advertisers the possibility of targeting those segments directly via the operator

FMCG Large Retailers

Description Potential Customers

Location Trend Reports Track trends in customers’ location and movements, and send period reports to clients

Real estate companies Public transport agencies Large retailers

Market Research Leveraging the customer base, as a proxy for the market to support customized market studies

Travel Agencies Banks Municipalities

Financial Fraud Detecting real-time CC and ATM fraud Banks Credit Card Companies

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Examples for External Monetization Use Cases

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Targeting the Right Use Case

Geography

Regulation

Maturity

Market

Need

Value

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Happening in the Industry

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AT&T Credit Card / ATM Fraud Detection

When a CC (or debit card) is either stolen or “duplicated” and used by another person in another location to purchase a good or withdraw cash

Identify in real time (when transaction is submitted) that the use of it is not performed by the card owner

Block the card from additional use and/or block the transaction

Solution is based on physical location of mobile device

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Verizon Location and Profiling

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Orange France Application for Business

Use Case Definition and Execution Example

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Defining Use Cases

Need

Customer

Value

Maturity

Privacy & Regulatory

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Transportation Example

Key Success Factors Understand potential partners’ business needs

Translate needs to relevant insights

Accurate and reliable data

Intuitive environment for data exploration

Establish a business model to accommodate partner’s maturity

Accompany your partners – key to a long-term success

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Analyze location data by providing statistics for predefined hotspots at any time range, enriched with subscribers' profile and usage data

Answer questions such as:

– Where are the most crowded hotspots?

– What are the potential locations for new hotspots?

– What are popular roaming visitors' locations?

– First timers vs. repeated visitors in different locations?

General Geographical Traffic Analysis

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Telco Added Value

Origin and destination definitions – based on

commuter movements and behavior

Origin/destination predictions - Given

origin/destination location and a certain time,

date and events, predict destination/origin in a

predefined time.

Commuter profile

Public vs. private journey

Real-time congestion

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Business Attributes

Enriched Commuter Profile Home Location Work/School Location PT Digital Habits Age Gender Interests Families and Social

Circles

Destination Prediction Algorithms

Waiting Time Calculations SWT AWT EWT

Origin & Destination Analysis Transfer Time Public

vs. Private

Density/Congestion By Station By route (Shape) By Location

Origin & Destination Analysis Journey Analysis Public Transpiration

Users

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Operators Data Sources: Subscribers Location

Location Based System Access points

Subscribers Profile CRM Advanced models

Subscribers mobile usage behavior Voice, Text, Data

Accessible Transportation Data Sources – Optional Real-Time data from GPS devices on vehicles SWT and other internal data sources

Data Sources

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3rd Party Portal

Intuitive UI

Analysis Capabilities

Required attributes

Reporting capabilities

APIs

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Home – Work/School Journey Pattern Identification

machine learning algorithms

machine learning algorithms

LBS Data

AP + LBS Data

LBS Data

AP + LBS Data

AP + LBS Data

LBS Data

LBS Data

Journey Analysis Duration

Distance

Cost

Congestion level

Dwell time

Walk time

Number of connections in journey

Etc.

Transfer Time: Public vs. Private

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Home – Work/School Journey Pattern Identification

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Congestion heat maps

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Possible Routs

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Rout Analysis

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Rout Analysis

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Rout Analysis

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Rout Analysis

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Rout Analysis

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Summary

Operators have huge amounts of data

The challenge is to monetize it

The Push strategy

− Learn the market needs

− Define and build the right solution

− Treat 3rd party as another customer we need to understand and propose the right solution

− Accompany your partners – key to a long-term success

Website RA Blog www.ra-blog.org

www.cvidya.com

Your Success is Our Business