IBM Audience Analytics for Broadcasters and TV Networks

© 2015 IBM Corporation

IBM Audience Insightfor Broadcast/Cable Networks

© 2015 IBM Corporation2

Agenda

introductions

industry highlights

audience insight opportunity

cable TV and broadcast views

the solution

why IBM?

© 2015 IBM Corporation3 © 2015 IBM Corporation3

Industry Insights


Dramatic Change

75% of people watchstreamed on-demand video

several times a week,

compared to 77% who watch

scheduled broadcast TV several times a week.

Average Net Promoter Score for OTT

on-demand services in the US is 39,

compared to just 12 for traditional

TV providers.

streaming is closing in on linear TV

strong preference emerging for on-demand

Source: http://www.ericsson.com/res/docs/2014/consumerlab/tv-media-2014-ericsson-consumerlab.pdf


marketing and advertising landscape is changing

of TV ad dollars will be spent via

programmatic TV products by 2018

20%

Gartner Hype Cycle 2015, eMarketier 2015

2015 spend on digital advertising by US

M&E industry

$6.2B

Make every advertising dollar count bypersonalizing the consumer experience



TV and video ads need to become more relevant, more personalized, and less intrusive.

Personalized ads perceived as more helpful.

30% want tailored service

offerings

30% are willing to pay to get rid of ads

40% would like to

actively specify the

ads they want

30% want personalized

recommendations

for content

50% say removing

ads is very important


Gartner urges clients to continue to closely track the progression of social network analysis, social media distribution and other metrics, dynamic

video ad insertion, and automatic content recognition (ACR)

- Gartner 2014

Analyst Insights

Digital consumer spending will overtake traditional consumer spending in 2015 and will be 26 percent larger by 2018.

- McKinsey & Company 2014


Social media’s influence is growing• 85% of people who tweet during primetime hours reported tweeting

about TV• 72% tweet while the show is on live• 60% tweet about shows when they are not actually watching them• 58% tweet about TV shows while they watch on time-shifted platforms• 90% took subsequent action such as watching a show after seeing TV-

related tweets

Source: https://blog.twitter.com/2014/study-exposure-to-tv-tweets-drives-consumers-to-take-action-both-on-and-off-of-twitter © 2015 IBM Corporation


Consumer experience and the trail of data is changing

9

360º View of the

Consumer

ERP and CRM Systems

Traditional Structured Data

Marketing Data

3rd-Party Audience / Market Research

Non-Traditional Data

Consumptionvia STB, VOD, IPTV, DVR

Public Data

Online Purchases& Interactions

Social Media

Behavioral Textual /Reviews

Audio/Video

Non-TraditionalUn-Structured Data

Email/Chat Correspondence


In this environment, driving differentiation with consumers through trust and relevance

is important

collect feedback social media analytics+

analytics enables you to know and treat consumers as individuals

engage

+

© 2015 IBM Corporation11Source: Forbes

Consumer Centric Approach

11

Understand how distribution windows impact content and ad valueIncreased information transparency between departmentsReal time visibility into ad inventory and ad valueUnderstand content preferences to tailor recommendations and ads

Access to 360-degree consumer profiles

New profits from the highest value customers


$8M new revenue

Cable TV company in the U.S. generated more

than $8M USD in new revenue from enhanced

DVR services and increased advertising

reach by 12%

of advanced analytics…the results

Near 100% accuracy

Leading online advertising network increased

accuracy to nearly 100% by analyzing complete

data sets, giving customers improved

projection of campaign performance

80% more ad revenue

Major publisher uses advanced analytics to

provide real-time insights into audience preferences, increasing total advertising

revenue by 80% in one year


The Opportunity for Audience Insight


Analytics represents an opportunity to drive value across multiple business functions

Experience

What are my consumers saying?

Monetize

How much is my content worth?

Create

What innovative content appeals to each segment?

Life

cycl

e

Distribute

On what platforms should I distribute?

Market

Am I generating the right message for target consumers?


•Predict outcomes (sales, views)

•Optimize the media mix

•Predict behavior

• Improve reach to target segments

• Increase campaign conversion

• Enable personalization

•Identify consumption drivers•Drive engagement, reduce churn•Calculate lifetime value

• Know audience characteristics/preferences

• Realize increased content value

• Improve targeted advertising

Consumer Targeting

Audience Forecasting

360º Consumer Profiling

Engagement & Churn

Analytics

Audience Insight is enabled through a suite of advanced data integration and analytical capabilities


Capability: 360 Consumer Profiling

360º consumer profiles audience micro-segments

3rd Party Audience

Digital Interactions

3rd Party Consumption

CRM & Call Center

Social Media

extract data/build profiles

entity marketing micro-segmentation

segment mapping

audience data modeling

Develop multi-platform audience data model

Match/de-duplicate consumers across sources/platforms

Aggregate individuals to form micro-segments

Map segments across multiple sources

Extract data from unstructured data to build profiles

Move beyond basic demographics to deep psychographics, interests & preferences


Capability: Measuring Engagement & Churn

segment consumers

define/extract variables

develop model

predict and respond

integrate and model data

Integrate all relevant data into a common model

Identify predictive variables by segment & extract

Develop models to measure & predict engagement/churn

Run model by segment & identify optimal response

Use statistical methods to segment consumers

3rd Party Attributes

Mobile & Web Behavior

Historical Behavior

CRM & Call Center

Social Media

segments & variables engagement & churn modelUnderstand & predict behavior to drive growth & retention strategy


Capability: 360 Consumer Profiling

engagement by segment targeted content delivery

measure engagement

develop target models

determine best action

Integrate & delivery

define target segment

Define target segments based on 360º profiles

Develop propensity, look-alike and optimization models

Run segments through models to find best action

Integrate with ops systems to deliver targeted content

Measure historic engagement across platforms

Target consumers across platforms & enable dynamic content delivery

EMM & campaigns

Mobile app & geo location

multi-platform engagement

360º profiles

Social Media


Capability: Forecasting and Optimization

predictive variables forecast & optimization

define/extract variables

develop models Tune & train models

predict & monitor

integrate & model data

Integrate all relevant data into a common model

Develop forecasting & optimization models

Utilize data to train model & test scenarios

Run model to predict and monitor results

Identify predictive variables & extract by source/segment

historical behavior

external market

multi-platform engagement

360º profiles

Social Media

Utilize historic data & real-time market signals to predict performance

© 2015 IBM Corporation20 12

is a radical departure from business-as-usual &

game-changing capabilities across the

content lifecycle

The resultSmarter

MarketingSmarter Content

Smarter Distribution

Smarter Advertising

Differentiated Experience


Cable Industry Use Cases


Cable: core use casesUse Case Challenge Solution

Churn Reduction

Declining revenues due to spikes in churn in the first 90-days and at promotion roll-off.

Analyze data for indicators of churn; develop predictive models to identify candidates and target them with retention offers.

Targeted Cross-Sell & Up-Sell

Lack of revenue growth due to inability to identify candidates for cross-sell & up-sell and deliver relevant offers.

Build rich customer profiles based on consumption behavior & look-alike modeling to target cross/up-sell offers to segments.

Targeted Advertising

Operations and IT are not equipped to resolve data quality & PII issues required for targeted ads.

Establish a secure analytics environment to integrate subscriber, STB and third-party, enriched data.

Avoidable Truck Rolls

Dispatching trucks to customer locations has high operational cost and is not always necessary.

Develop a model to predict avoidable truck rolls using care, network and billing data and divert requests to alternative challenges.

First-Call Resolution

Customer communications are not integrated across channels leading to redundancy and poor service.

Implement intelligent call routing to diagnose root cause of inbound calls using IVR and other structured & unstructured sources.


Potential value exceeds $100M annually

Boost CPM Manage

yield & stewardship

Pote

ntia

l Val

ue to

MVP

D (M

illio

ns)

Increase Subs

Grow ARPU Total Annual

Value From Analytics

Reduce onboarding churn

Reduce churn at promotion roll-off

Increase cross-sell & up-sell

Improve campaign conversion rates

Assumptions:Based on analysis of publically available data from SEC filings (Comcast, TWC, Charter, DirecTV, Dish). Benchmarks based on IBM analysis, case studies and third-party research.

Boost Ad SalesReduce

OpEx Reduce

contact center costs

Eliminate avoidable truck rolls


reduced churn with targeted offersNeed•unusual spike in customer churn during onboarding & promotion roll-off•little visibility into which customers to target with retention offers

Benefits•Churn predictors identified•Put focus on high-value target segments•Integrated models into marketing system to dynamically deliver retention offers


Case Study:Leading cable provider


Broadcast TV Industry Use Cases


Use Case Challenge Solution

Influencer Identification

Bulk of audience is unknown making it difficult to target campaigns that drive tune-in and the water-cooler effect

Integrate social media data to identify influencers & target them with campaigns

Fan Scoring & Targeting

Lack of visibility into audience engagement week-to-week (acquisition, retention, churn)

Combine 1st & 3rd party data sources with recency/frequency models to measure engagement, churn and target campaigns

Campaign ROI Analysis

Inability to gauge campaign effectiveness & ROI on promo media & marketing spend

Correlate direct & indirect stimuli from linear & non-linear sources over time to assess the impact of campaigns on tune-in

TV Everywhere App Analysis

Traditional measurement tools are not equipped to handle direct consumer interaction data from apps

Integrate app streams into measurement models to assess adoption, authentication, time spent and other KPIs

Audience Micro-Segmentation

Traditional sources of audience data do not cut across platforms or support the deep demographics that advertisers covet

Integrate multiple sources of 1st & 3rd party, enriched data, and social, to build 360º profiles and custom segments

Ad Yield Optimization

Lack of transparency & integration between linear & digital ad platforms results in yield inefficiencies

Manage inventory yield & stewardship to satisfy contract obligations & maximize effective CPMs

Broadcast TV: core use cases


Potential value exceeds $65M annually Boost

effective CPM Manage yield &

stewardship

Pote

ntia

l Val

ue to

Net

wor

k (M

illio

ns)

Improve Efficiency

Grow Audience

Total Annual Value From Analytics

Elimination of redundant platforms, tools, sources

Improved reporting cycle times

Target addressable audience

Drive increased tune-in on primetime

Assumptions:Based on analysis of publically available data from SEC filings (CBS, NBCU, Fox, Disney Networks, Viacom, Time Warner). Benchmarks based on IBM analysis, case studies and third-party research.

Maximize Value


built an audience insightintegrated platform Need•data sources stuck in organizational siloes & data fragmented across platforms •limited visibility into newly launched TV Everywhere app •long cycle times for audience research and sell sheet creation for ad sales

Benefits•integrated 40 viewing data sources •developed data discovery & analytics•enabled rapid sell sheet creation •eliminated spend on third-party data

Case Study:Leading US Broadcaster


Studios Use Cases


Studios: core use casesCaseUse Case Challenge Solution

Film Budget Allocation

Rising production & marketing costs require a more targeted approach for marketing strategies: mass-market or niche, genre release

Analyze ROI to optimize spend for production and marketing budgets

Creative Tuning

Increasing reliance on big budget tentpole releases means high stakes for studios

Analyze trend and chatter to adjust creative elements to increase commercial viability

Greenlight Analysis

Increasing reliance on big budget tentpole releases reduce number of films released and increase stakes associated with greenlighting

Analyze creative elements against historical data & current trends to understand demand for films

Word of Mouth Optimization

Rapid spread of positive or negative sentiment via social media and fan sites determine box office success, despite marketing efforts

Combine 1st and 3rd party data sources to identify and target key social influencers

Window Optimization

Falling home entertainment revenue means more pressure to succeed in the theatrical window in order to drive downstream sales

Manage content inventory yield across release windows and geographies to maximize lifetime revenues

Licensing Optimization

Digital and video-on-demand capabilities are changing consumer behavior, and challenging traditional release windows

Analyze Back Catalog to identify optimum pricing and bundles to increase revenue from all licensing channels


Potential value exceeds $80M annually or $5M per film real value is in ability to identify and avoid major flops

Drive demand for long tail content

Optimize distribution

Pote

ntia

l Val

ue to

Net

wor

k (M

illio

ns)

Improve Efficiency

Grow Audience Total Annual

Value From Analytics

Budget allocation optimization

Reduced costs and increased investment yield

Grow foot traffic through targeted advertising

Identify new audiences

Assumptions:Based on analysis of publically available data from SEC filings (Fox, Disney, Paramount, Warner Brothers, Universal Studios). Benchmarks based on IBM analysis, case studies and third-party research. Does not include uplift from Green Light Analysis, Creative Tuning, and Window Optimization

Maximize Value


uses social indicators to predict opening box officeNeed•Rising production and marketing costs created high stakes; must recoup costs•Increasing reliance on big budget tent pole films meant fewer movies with larger investments•Marketing efforts had limited targeting

Benefits•Analytics predicted opening weekend box office within with 72% accuracy •Identified most influential social channels to drive targeted media investment

Case Study:Top grossing film studio


Technical & operational limitations within current data architecture

Master Data Management

De-duplicated customer informationReference data & cross-system code mappings

Master Data Repository

Data Security & Governance

Data lineage & impact analysisData privacy & security

Warehousing

•High-concurrency historical queries

•Limited granularity

•Long-running data processing

EDW

Analytics & Reporting

Zone

Data Integration

•Batch (daily) movement•Only structured data

Batch Reporting

Limited, DisjointedSearch & Discovery

LimitedDescriptive& Predictive

Models

Metadata Repository

Marts

ODS

•Granular data•Limited history

Limited Business Actions

Siloed DataConnectors

CRM

Marketing

App usage

Social Media

Location

Behavioral

Limited Targeting

Mediocre Customer Experienc

e

Consumption

ERP


The SolutionBehavior Based Audience Insight


Predict and decide the best action

Cognitive computing

Intuitive analytics for everyone

Analytics as and when you need it

TRADITIONAL APPROACH

the realm of the specialist

BIG DATA & ANALYTICS APPROACH

embedded in everything


Scheduled


Real-time


Pre-programmed analysis on structured data


Learn to sense and predict using all types of information


What has happened and why


What will happen and what should you do


Embracing new paradigms to be more consumer-centric

360º Consumer Profiling

Engagement & Churn Analytics

Consumer Targeting

Forecasting & Optimization

Topic-Based Influencer Targeting

Real Time Mobile Campaigns

Multiplatform Measurement

Engagement Scoring

Ad Yield Optimization

Demand Forecasting

Profile Entity Matching

Psycholinguistic Profiling

Match millions of social media and CRM profiles to develop audience micro-segments

Normalize data across platforms to get integrated view of consumer behaviors

Classify viewers based on engagement to compare growing/waning passion

Build cross channel optimization models for targeted ads to maximize yield of sold ad inventory

Identify significant predictors of consumer demand in order to develop forecasts

on new media content

Trigger timely, targeted mobile promotions based on real-world events

Identify most influential audience members for specific topic and re-target look alikes

Analyze text posts to analyze & extract underlying intrinsic psychographic traits,

value, & needs


A Next Generation Advanced Analytics Platform New / Enhanced

ApplicationsAll Data

ERP

CRM

Marketing

App usage

Social Media

Location

Subscriber profile

Multi-Channel Measurement

Campaign Management

Ad Sales Optimization

Churn Management

Distribution Optimization

Content Recommendations

IBM Watson Foundations

Big Data & Analytics Strategy, Integration & Managed Services

Big Data & Analytics Infrastructure

What’s happening?Discovery

Why did it happen?Reporting &

analysis

What could happen?Predictive analytics

What’s best?

Cognitive

What action should I take?

Decisions

Information Integration & Governance

Landing, Exploration & Archive data zone

EDW & data mart

zone

Operational data zone

Real-time Data Processing & Analytics

Deep Analytics data zone

Consumption


Advanced Analytics Platform core technical componentsNew / Enhanced

ApplicationsAll Data

ERP

CRM

Marketing

App usage

Social Media

Location

Subscriber profile

Multi-Channel Measurement

Campaign Management

Ad Sales Optimization

Churn Management

Distribution Optimization

Content Recommendations

IBM Watson Foundations

Big Data & Analytics Strategy, Integration & Managed Services

Big Data & Analytics Infrastructure

What’s happening?Discovery

Why did it happen?Reporting &

analysis

What could happen?Predictive analytics

What’s best?

Cognitive

What action should I take?

Decisions

Information Integration & Governance

Landing, Exploration & Archive data zone

EDW & data mart

zone

Operational data zone

Real-time Data Processing & Analytics

Deep Analytics data zone

Consumption

Stream Computing

Hadoop Analytics

Data Collection/ Integration

Discovery Platform

Business Intelligence

Decision Management

Predictive Analytics

Cognitive NLQ

Data Warehouse

Marketing Optimization


Platform Capability IBM Products How It Powers IBM Audience Insight SolutionData Collection & Integration

Infopsphere Information Server

Tap into core content delivery networks to collect, integrate, and analyze click stream or other IP based data

Stream Computing & Analytics

InfoSphere Streams Provide real-time triggers for ad targeting or marketing campaigns based on audience media behavioral patterns

Hadoop Analytics System InfoSphere BigInsights Analyze millions of social media posts to extract and build audience demographic, lifestyle, and brand affinity profile attributes.

High Performance Data Management & Warehouse

IBM PureData System Extremely fast “slicing and dicing” of consumer/audience behavioral data and deployment of audience micro segmentation models

Discovery & Exploration Platform

Watson Explorer Enable business user search, browse, and filtering of audience segments to compare/contrast across media content (TV Shows, etc.)

Business Intelligence Cognos BI Analyze and track operational or sales data from marketing campaigns or ad operations or sales systems

Cognitive NLQ Watson Analytics Perform natural language queries to explore or identify evidence to formulate hypothesis for content performance or audience response.

Predictive Analytics SPSS Develop segmentation, clustering, affinity analysis and build models to support demand forecasting, targeting, and recommendations

Decision Management SPSS, iLog Determine suitable promotional campaign or ad for target audiences

Marketing Optimization IBM Campaign Design & execute marketing campaigns tailored to needs & preferences

IBM’s Analytics Platform includes these “best of breed” components


Data WarehouseDB2 with BLU Acceleration, BLU Acceleration for Cloud DB2 Analytic Accelerator PureData System for Analytics PureData System for Operational Analytics Industry Models

Landing, Exploration and Archive data zone InfoSphere BigInsights for Hadoop PureData System for Hadoop Content Manager Case Manager Content Navigator

Information Integration & Governance InfoSphere Optim InfoSphere Guardium InfoSphere Data Privacy for Hadoop InfoSphere Information Server InfoSphere Data Replication InfoSphere Federation Server InfoSphere Master Data Management Cognos Command Center

Reporting and analysis Cognos Business Intelligence Cognos Express Business Intelligence Pattern Cognos BI Pattern with BLU Acceleration

Real-time Data Processing & Analytics SPSS Modeler Gold Operational Decision Manager ILOG CPLEX Optimizer Decision Optimization Center InfoSphere Streams InfoSphere Sensemaking

Discovery & Exploration Watson Analytics Watson Explorer SPSS Analytic Catalyst & SPSS Analytic Server InfoSphere Business Information Exchange

Content Analytics Content Analytics SPSS Data Collection Social Media Analytics

IBM Watson Foundations Architectural Product Portfolio

Planning & Forecasting Concert Cognos TM1 Cognos Insight Cognos Express Cognos Controller

Operational data zone DB2 with BLU Acceleration IMS PureData System for Transactions Informix, Informix TimeSeries InfoSphere Master Data Management

Predictive analytics and modeling SPSS Statistics SPSS Modeler Concert Cognos TM1 Cognos Insight Cognos Express Cognos Controller


Why IBM?


Why choose IBM for media and entertainment solutions?

Industry expertiseBuilt for the M&E industry

Unparalleled analytics expertiseResearch Analyst Market leader

Advanced analytics and integrationdeliver a single view of analytics across the enterprise

Commitment to innovationIBM global research and service organizations

Flexible deployment options faster time to value and lower cost of ownership

Over $16B in information & analytics related acquisitions of “best of breed” technologies

Patented Unification of Descriptive, Predictive and Prescriptive Analytics APIs Enable Simplified Application Development

Spent $50B on R&D in the last decade

On-premise, SaaS, Cloud, Hybrid

Global clients representing $6b+ business in Telecom, ISPs, Cable TV, Direct to Home Satellite, Broadcast Networks, related segments


IBM Research unique inventions that will bring great business valueIntelligent Customer

ProfilesPsycholinguistic

AnalysisLife Event Detection

Behavioral Pricing


Let’s get started

Add to roadmap & secure investment

Design & implement at enterprise scale

Integrate with operational systems

Test performance Train/enable users Operational go-live /

bring to market

Implement / Scale

Define desired outcomes

Gather high-level requirements

Scope POC Quantify value

potential & estimate costs

Validate assumptions

Determine ROI & metrics for tracking

Go/no-go on POC

Scope & Value Assessment

Identify potential analytics initiatives

Define business value

Describe business & technical capabilities

Prioritize based on value and ease of execution

Assign initiative owners and SME’s

Analytics Discovery

Establish discovery environment

Define requirements & solution design

Ingest required data & develop POC

Test output against success criteria

Evaluate results and prove the value

Go/no-go on implementation

Pilot / POC



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IBM Audience Analytics for Broadcasters and TV Networks