Evolving the Service with Audience Measurement. A presentation by Marc Price, CTO Americas with Openet. Learn more about our audience measurement solution at https://www.openet.com/what-we-do/business-intelligence/audience-measurement

1. Real-time Decisioning for Big Data:
Evolving the Service with Audience Measurement
Presented by Marc Price, CTO Americas
July 2014

2. 2w w w . o p e n e t . c o m
© Copyright 2013 Openet – Company Confidential
For Use Under Non-Disclosure Only
Openet delivers the infrastructure to enable
Operator Innovation
A global leader with more
than 80 customers in 32
countries, Openet
provides insight,
interaction, control, and
monetization within the
world's largest and most
complex networks.
Openet helps control costs and increase
revenue by enabling customers to innovate
how people, machines and services
engage with their network
Openet helps increase revenue and
control costs by enabling customers to
innovate how people, machines, and
services engage with networks
Cable
Mobile
Machines
People
ServicesFixed
Real-time
transaction
management

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© Copyright 2013 Openet – Company Confidential
For Use Under Non-Disclosure Only
• Service Data and Customer Data can be leveraged in
unprecedented ways to drive revenues, increase loyalty, and
reduce costs
• New techniques for big data require real-time processing for low
latency analytics, as well as pre-processing for batch analytics
• An example of valuable analytics for service usage is audience
measurement for video viewing across various platforms
• New techniques enable streaming event processing, in-memory
No-SQL storage, real-time decision triggers, and holistic data
delivery for personalized services, recommendations, analytics,
dashboards, and beyond
Highlights

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© Copyright 2013 Openet – Company Confidential
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The Digital Communication Age
The volume and variability of immediately available offerings make the communication
decision-making environment quite distinct from other billable services.
The Challenge is to maximise every interaction Experience
Interaction Types:
• Ad hoc
• Occasional
• Informative
• Social
• Regional
• National
• International
• Short term
• Regular
• Excessive
Interaction Types:
• Information
• Entertainment
• Purchasing
• Business
• Social Media
• Messaging
• Browsing
• Posting content
• Gaming
• Tweeting
• Communication

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© Copyright 2013 Openet – Company Confidential
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Growth of Personal Data
This richness of big data provides an enormous potential to personalize services - yet
customers still marvel at how little their service provider seem to know them
The volume of personal data is
growing exponentially & at a
staggering rate to the actual
number of subscribers
Per Subscriber
Personal Data
My Plan
My usage
My spend
My Contacts
My devices
My fav apps
I’ve been a customer for
years… I never receive any
relevant offers… I want more
interactive, informative contact

6. 6w w w . o p e n e t . c o m
© Copyright 2013 Openet – Company Confidential
For Use Under Non-Disclosure Only
1998
Prepaid
2000
GPRS
Unleash the power of real time personalization
Despite the vast amount of customer data that exists, marketing continues to rely on traditional
segmentation schemas and static profile attributes that provide an incomplete view of the customer
• Traditional BI systems, data warehouses
and CRM systems are ill-equipped to
support dynamic customer profiling
• Operators know they are not reaching
certain groups of people, and may not even
identify a “category” before it is too late
• Legacy systems are not designed to deal
with the volume, variety, velocity and
volatility of big data to deliver value,
relevance and immediate responses to
market needs
2005
3G
2015
HetNets
2013
LTE
2014
IMS
1996
2G/ GSM
Patchwork of legacy infrastructure
supporting the evolved technology &
services. Optimizing subscriber profit
margins is now a fine art with rising
infrastructure OPEX costs
2007
HSDPA
2010
WiFI
OPEX

7. 7w w w . o p e n e t . c o m
© Copyright 2013 Openet – Company Confidential
For Use Under Non-Disclosure Only
Seizing the Moment
Analytics insights require useful and actionable information through
timely actions to process data when it is most relevant
Tier 1
(first order
Analytics)
Tier 2
(second
order
Analytics)
Tier N
(nth order
Analytics)
Tier 1
(first order
Analytics)
Location A
Location B
Window of Insight
Window of Insight
Window of Insight
ADS
Triggers
Batch
ie. Instructing Policy Use Cases,
Recommendations
Insights
Insights
Insights
Status
Scenario Elligibility
Condition A
Condition B
Condition C
Condition X
<15 milliseconds
1 second
15 seconds




For a particular subsriber:
Continuous stream of data
ADS: Advertising Decision Server
ie. Ad Decisions
ie. Lifecycle analytics

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© Copyright 2013 Openet – Company Confidential
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Operators are seeking Reporting and Analytics solutions in response to new business drivers
Delivering value, relevance and immediate response
• Intelligent Upsell use cases: creating more
relevant, timely and personalized services
Real Time Decisioning
• Real time behavior visibility & detection of
network service impacts and billing impacts
Real Time Service Assurance
• Enable content provider sponsored data,
Relevant advertising, B2B revenue chains
Sponsored Data and
Advanced Advertising
• Understanding viewing impressions and
related applications usage to aid with
marketing, upsell and content negotiations
Audience Measurement
Some Examples:

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© Copyright 2013 Openet – Company Confidential
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Detailed video viewing impressions and contextual usage statistics better support
marketing and advertising campaigns as well as content negotiations
Case Study: Audience Measurement
Audience measurement incorporates analytics for:
• Linear television program viewing
• Video on demand viewership
• Ad campaign viewership
• Interactive content engagement

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© Copyright 2013 Openet – Company Confidential
For Use Under Non-Disclosure Only
Detailed video viewing impressions and contextual usage statistics better support
marketing and advertising campaigns as well as content negotiations
Audience Measurement: Challenges
Challenges include:
• Normalization across traditional cable systems and IPTV and other platforms
• Correlating usage for “Second screen” and multiple devices with linear viewing
• Household vs. Individual user data
• Protecting Personally Identifiable Information (PII)
• Supporting Data Governance techniques

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© Copyright 2013 Openet – Company Confidential
For Use Under Non-Disclosure Only
Enables operators to generate subscriber profile and segmentation with unprecedented
depth and accuracy
Audience Measurement: Highlights
Usage information is validated, normalized across platforms, then enriched with
marketing & subscriber information handling opt-in/out for behavioral viewing metrics.
The solution collects and correlates second-by-second click stream, linear TV
viewing, on-demand and interactive TV events.
Delivers profile information across systems in a useful, anonymous format to internal
and third-party marketers, advertisers and buyers to enable the planning and
measurement of addressable advertising campaigns and marketing promotions

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© Copyright 2013 Openet – Company Confidential
For Use Under Non-Disclosure Only
Audience Measurement: Architecture
Data Sources:
ActIngest Analyze
Ad campaigns
HSD
Events
Wireless
Data
Events
Linear TV
Tuning
Events
VOD/PPV
Events
iTV
Events
DVR
Events
Ad Inserts
TVE
Events
Filtering
Parsing
Validation
Translation
Aggregation
Correlation
Enrichment
Multi structured
data for streaming
and batch analytics
Data Collection &
Processing
Content rights negotiation
Marketing campaigns
Recommendations
Real Time Insight
Data Analyzed in
motion
Storage

13. 13w w w . o p e n e t . c o m
© Copyright 2013 Openet – Company Confidential
For Use Under Non-Disclosure Only
Measure and influence customer behavior
• Measure:
• Geographic/Demographic Trends
• Screen/Device Usage trends
• Ad Viewing Trends
• Content Viewing Trends
• Content Ratings
• Influence:
• Ad Placements and pricing and therefore Ad Revenue
• Content Pricing driving content revenues
• Targeted Offers driving improved service uptake and revenues
• Recommendations driving increased usage revenue
Big Data techniques applied to Video Viewership enable
service providers to:

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© Copyright 2013 Openet – Company Confidential
For Use Under Non-Disclosure Only
Conclusions
• Improved Customer Satisfaction
• Boost in Loyalty
• Reduced Costs
New techniques for managing service usage data enable: