Device proliferation, shifting distribution channels, and the popularity of social media are driving meaningful changes in consumer behavior that affect nearly every aspect of the TV business. This report explores the phenomenon of “TV Everywhere," and includes research on the drivers of this new disruption, four use cases, and actionable strategies to address the challenges and opportunities. Download the full report at: http://bit.ly/altimeter-report-big-data-tv

1. Data Everywhere:
Lessons From Big Data in the
Television Industry
By Susan Etlinger
with Rebecca Lieb and Jaimy Szymanski
Includes input from 18 ecosystem contributors
A Market Definition/Best Practices Report
July 10, 2014
Preview Only

2. Drivers of Disruption and Insight ................................................................................................................................................................
Industry Drivers ....................................................................................................................................................................................................................
Consumer Behaviors ..........................................................................................................................................................................................................
Business Impacts ...............................................................................................................................................................................................................
Using Data to Drive Competitive Advantage ...............................................................................................................................
Programming .........................................................................................................................................................................................................
Distribution ............................................................................................................................................................................................................................
Promotion ...............................................................................................................................................................................................................................
Ratings and Performance Evaluation ............................................................................................................................................................................
Data Sources and Implications ......................................................................................................................................................................
Best Practices and Recommendations ..............................................................................................................................................
Coming Up Next ...................................................................................................................................................................................................................
Table of Contents
In 1951, Desi Arnaz of I Love Lucy fame made a decision that would signal the birth of
modern television. Rather than film the show with a single camera, as had been done up
to that point, he decided to use multiple cameras so he could shoot before a live audience,
ushering the “reaction shot” into television and creating a more vibrant, realistic, and
cinematic television experience.
While the television industry has changed dramatically since then, spurred by device
proliferation, changing distribution methods, and the increasing popularity of social media,
the rise of “TV Everywhere” and the resulting availability of new streams of digital data
represent a new resource for business models already in transition.
This report will examine four use cases for data to better understand this new technology
landscape and will lay out practical strategies that executives can use to address the
resulting opportunities and risks.
Executive Summary
Preview Only
3
3
5
7
8
9
9
10
13
14
14
16

3. As a result of these new dynamics, the television industry is gaining access to a
broad range of signals that can be used to inform decisions from programming
to promotion to distribution to ratings. Following is a summary of the three
most prominent factors shaping the industry today: device proliferation, multiple
distribution methods and disparate social media platforms.
Industry Drivers
A recent episode of AMC’s Mad Men, featuring the 1969 moon landing, depicts
the pattern that dominated TV viewing until quite recently. Families, colleagues,
friends, and neighbors would gather around the set and communally watch an
event or a show, on a single device, at the time it was broadcast.
Today, the advent of multiple devices, distribution methods, and social media
platforms has shattered this model. Television viewing is multidimensional.
It’s multi-device, time-shifted, and often non-linear (or hyper-linear, e.g., binge
viewing). It’s no longer passive entertainment; television is characterized by
active viewer participation via social media sharing, commenting, and User-
Generated Content (UGC).
As a result, the industry is simultaneously grappling with a range of
dynamics. Audience fragmentation can be both a curse (lack of insight) and
a blessing (ability to personalize). Ratings methodologies and traditional KPIs
no longer reflect today’s reality. Content creation can be an organizational
burden, a competitive advantage, or both.
Data Everywhere: Lessons From Big Data
in the Television Industry
3
Drivers of Disruption and Insight
We’ve come a long way from the early days of television.
Today’s viewers watch Scandal with mobile device in hand
for a true second-screen experience, binge on Orange Is
the New Black, create memes and other user-generated
content from Game of Thrones and Breaking Bad, and chat
on Twitter with their favorite Being Mary Jane characters.
Family members watch their favorite programming
individually on their own devices.
Today, the advent
of multiple devices,
distribution
methods, and social
media platforms
has shattered this
model. Television
viewing is
multidimensional.
It’s multi-device,
time-shifted, and
often non-linear.
Preview Only

4. 4
Multiple disparate data streams may strain
organizational culture, providing a piecemeal view
of audience attitudes and patterns, or they can be
leveraged to better understand audience behaviors
and attitudes and to gain competitive advantage.
Following is a view of the primary industry trends
at play, their impact on consumer behavior, and the
resulting pressures and opportunities for business.
Device Proliferation
While in days past the “TV” referred to a single
device, today’s audiences have access to TV virtually
everywhere: on their computers, tablets, smartphones,
and even gaming consoles. This trend continues to
accelerate; a recent report by CMO.com states, “TV
Everywhere authenticated video from gaming consoles
and OTT devices grew 539% year-over-year.”1
Some of the biggest changes in the market result
from the fragmentation of audiences among these
devices, and the insights and blind spots this
fragmentation provides. Some organizations struggle
to make sense of disparate data streams, while
others see data as an opportunity to identify emerging
audience attitudes and behaviors. More than anything,
however, the availability of data at a device level
places a different lens on the TV viewing experience,
one that can provide insight in both directions.
Multiple Distribution Methods
While cable has been disrupting network television
for decades, and Web and mobile browsers aren’t
exactly new, the past few years have seen accelerated
fragmentation as streaming players, such as Apple
TV, Aereo, Roku, Redbox, Amazon Fire, Google TV,
and others, have gained popularity.2
CMO.com further
states, “Online video consumption across mobile
devices (smartphones and tablets) is at an all-time
high of 25%, with 57% year-over-year share growth in
the U.S. (Q1 2013 vs. Q1 2014).”3
While time shifting has been possible since the advent
of the VCR, what’s different now is that it’s delivered
via streaming, and therefore trackable. Now when
audiences time-shift and binge-view programming,
cable and satellite companies can detect and learn
from viewing patterns in a way that was previously
not possible. They can see how many minutes of a
show a viewer watches, whether they watch a single
episode in one sitting, or whether they run through
Source: Altimeter Group
Figure 1 Industry Drivers, Consumer Behaviors Spur Disruption and Insight
Preview Only

5. 5
three or four (or more) episodes per night. They can
see whether audiences grow or shrink after the first
few episodes or from season to season and adjust
plans accordingly.
Social Media & Social Data
Social media — and the content and data it generates
— are having a profound impact on the television
industry. At the most basic level, phenomena such as
rating, sharing, liking, retweeting, and other forms of
structured and unstructured data sourced from social
media and proprietary platforms have created a dialog
among programmers, distributors, and networks —
and even between artists and the audiences they
desire to reach.
This represents a huge potential source for market
research, albeit one that is substantially unmediated
and requires intensive processing, analysis,
and integration with other data streams to yield
meaningful insight. Beyond likes and shares, however,
the emergence of user-generated content has
added a new dimension to the viewing experience.
In addition to consuming entertainment content,
audiences can be avid makers as well, editing,
mashing up, and otherwise recontextualizing the
shows that interest them, whether in video, photo, GIF,
fan fiction, or other form.
HBO’s Game of Thrones is a frequent recipient of
fans’ adoration and creative energy, some of which
can begin as true UGC and remain so and some of
which can be commissioned as branded content if
advertisers discover that the creator’s work resonates
with their audience. One example of this is a recent
video commissioned by Blinkbox, Tesco’s streaming
service, which was timed with the announcement of
the availability of Season Four of Game of Thrones.
The video, “The Pugs of Westeros,” features a group
of pugs dressed in Game of Thrones characters. It
garnered more than 1.3M views in its first three days.4
Beyond the use of UGC itself, the data it generates
with regard to views, reach, sharing behavior,
sentiment, and other attributes provides useful
insight into potential promotion strategies within a
fragmented and increasingly socially connected world.
For example, what topics and characters do people
tend to recreate most often? On what platforms?
In what medium? That could become an input to a
promotion strategy or to the next season’s trailer.
Consumer Behaviors
A recent Nielsen report entitled The Digital Consumer
reveals the extent to which digital technology has
permeated media industries. “As a result of the
explosion in digital and mobile device ownership,”
it reads, “American consumers are connected with
screens throughout the day and engage with media
content for more than 60 hours per week.”5
More than the sheer amount of screen time, however,
consumer behaviors have emerged that carry the
potential both for unprecedented insight and for
challenges in sourcing, processing, and interpreting
the data. Following are the most salient examples
of these new behaviors, as well as examples of their
impacts (see Figure 2).
Preview Only

6. 6
Figure 2 Emerging Consumer Behaviors Create Data Opportunities and Threats
Source: Altimeter Group
Behavior Description Data Impacts
“BYOD for the
Family”
Coined by Carri Bugbee, refers to the phenomenon
in which individual family members watch their
own programming on their own personal devices.
Enhanced information about individual family
members’ preferences and behaviors.
Binge Viewing Watching television for longer time spans than usual,
usually of a single television show. (Wikipedia)
Which programs are binge-worthy, suggesting
high engagement/preference.
Cord-Cutting/
Delaying
Canceling a cable or satellite TV subscription in
favor of other methods of accessing content.
Preferred devices, times, locations for viewing
content.
Over-the-Top
(OTT) Content
Delivery of audio, video, and other media
over the Internet without a multiple system
operator being involved in the control or
distribution of the content. (Wikipedia)
Browser-dependent. Multiple System Operator
(MSO), i.e., cable or satellite provider, loses direct
access to data and is dependent on other data
sources for consumer viewing habits.
Place-Shifting Recording video or audio programming to view
or hear it in another location. (ITV Dictionary)
Location: Where people watch particular shows;
at home, during likely commute hours, in multiple
locations. Experience: What shows they place-
shift versus others.
Second Screen
Viewing
The use of an additional monitor (e.g., tablet,
smartphone) while watching TV. It allows
the audience to interact with what they’re
consuming, whether it’s a TV show, video
game, or movie. (Mashable)
Which types of programming prompt
conversation during airtime. Scandal is an
example of a network show around which this
behavior is prevalent. Awards shows and sporting
events also prompt second-screen behavior.
Social Actions Liking, favoriting, retweeting, starring, or
otherwise showing preference for a social
post. Social actions require the use of code (a
button) that generates structured data.
Requires correlation with other data sources
(other social networks and viewer data, for
example) to demonstrate anything other than
momentum on a single channel.
Social Comments Commenting on a post or posts on a social
network. Unlike social actions, social
comments are expressed in natural language
(unstructured data).
Unstructured data requires strong text analytics
to interpret and may also require some human
involvement, but it is a direct, albeit, raw source
for consumer attitudes.
Social Sharing The practice of sharing content from a website
on a social media site or application. (Google)
A signal of advocacy, which requires analysis to
determine impact on audience acquisition.
Time-Shifting Recording video or audio programming to view or
hear it at another time. (ITV Dictionary)
When people watch particular shows: time of
day/week. What shows they time-shift.
TV “Super
Connectors”
TV Super Connectors must do any of the
following “several times a day”: follow TV shows
on social media; following actors/personalities
on social media; communicate about TV shows
and/or characters on social media. (CRE Talking
Social TV 2: September–October 2013)
In a word, influencers, but this is a specific
definition. Super Connectors may or may not
be popular, but network analysis can reveal
their impact on audience sentiment and/or
acquisition.
TV Everywhere An initiative to provide controlled access to pay
television (cable, satellite) customers across
multiple device platforms. The concept is based
on the capability of the content provider to verify
the end user’s identity and authorization to
access content. (Source: Akamai)
Multiple, disparate data streams from devices,
distribution channels, social media, third-party
sources, and others must be viewed in context to
provide real insight.
User-Generated
Content (UGC)
Any form of content, such as video, blogs,
discussion form posts, digital images, audio files,
and other forms of media, that was created by
consumers or end users of an online system
or service and is publicly available to other
consumers and end users. (Webopedia)
Shows prompt engagement that requires
commitment, such as videos, fan fiction, GIFs,
images, or others. The tone and topic of UGC can
also provide insight into sentiment related to the
show’s story or actors.
Preview Only

7. Preview Only
To download this report in full at no cost, please visit our website at:
http://bit.ly/altimeter-report-big-data-tv

8. Authors
How to Work with Us
Altimeter Group offers a number of ways to engage with us, either by project or on a more ongoing basis. One
example is the Social Data Intelligence (SDI) Roadmap, a tool for business leaders who are using, or plan to use,
social data to help guide business decisions. The SDI Roadmap is built on an Altimeter Group maturity model
that is based upon detailed interviews with social data users and technologists. The model proposes a holistic
approach to social data use across the enterprise — taking into account data gathered from multiple enterprise
sources, such as Customer Relationship Management systems, Business Intelligence, and market research, and
lays out a set of criteria for organizational maturity.
Deliverables from the SDI Roadmap include a Social Data Intelligence Scorecard and accompanying maturity
model for social data strategy, as well as actionable recommendations for minimizing risk and improving overall
business performance.
To learn more about the SDI Roadmap, contact Leslie Candy at leslie@altimetergroup.com or 617.448.4769.
Susan Etlinger (@setlinger) is an Industry analyst at Altimeter Group,
where she works with global organizations to develop big data and
analytics strategies that support their business objectives. Susan has
a diverse background in marketing and strategic planning within both
corporations and agencies. Find her on Twitter at at her blog, Thought
Experiments, at susanetlinger.com.
Altimeter is a research and
consulting firm that helps
companies understand and
act on technology disruption.
We give business leaders the
insight and confidence to help
their companies thrive in the
face of disruption. In addition to
publishing research, Altimeter
Group analysts speak and
provide strategy consulting
on trends in leadership, digital
transformation, social business,
data disruption and content
marketing strategy.
Altimeter Group
1875 S Grant St #680
San Mateo, CA 94402
info@altimetergroup.com
www.altimetergroup.com
@altimetergroup
650.212.2272
Rebecca Lieb (@lieblink) is an analyst at Altimeter Group covering digital
advertising and media, encompassing brands, publishers, agencies
and technology vendors. In addition to her background as a marketing
executive, she was VP and editor-in-chief of the ClickZ Network for
over seven years. She’s written two books on digital marketing: The
Truth About Search Engine Optimization (2009) and Content Marketing
(2011). Rebecca blogs at http://www.rebeccalieb.com/blog.
Jaimy Szymanski (@jaimy_marie) is a Senior Researcher with
Altimeter Group. She has assisted in the creation of multiple open
research reports covering how disruptive technologies impact
business. Jaimy has also worked with Altimeter analysts on varied
research and advisory projects for Fortune 500 companies in
the telecomm, travel, pharmaceutical, financial, and technology
industries. Her research interests lie in social TV, gamification, digital
influence, and consumer mobile.
Preview Only