Why is big data relevant to media. Opportunities and challenges for media companies

1. (Big) data and television business
models
December 2015

2. The Guardian: adapt in real time the location on articles on the web
pages based on views
The Economist: identify customers likely to cancel their subscription
and propose special conditions
Publishers use the most highlighted sentences in an e-book in their
advertising material
CNN uses Dataminr as an “early warning system” of news
DVR: subscribers that record music channels receive pay-per-view
concert offers
Sky airs different advertising to different sub-segments of its viewers
In a world of abundance, big data links content, consumers and context
The Figaro uses data for its on-line readers to qualify its e-
commerce services
“Five or six years ago we started a new media model, charging for access through a metered
system. When we started doing that, it was primarily to build a revenue stream online, but
probably what was more important over time was the data and customer insight that that
gave us. That’s what transformed the business,”
John Ridding, Financing Times

3. • Increase customer/viewers base
• Increase sales of content
• Increase up-selling and reduce churn
• More efficient ad-sales
• More efficient content commissioning
• Ancillary revenues
Use of big data:
• Content acquisition
• Offer/line-ups, catalogues
• Targeted advertising and automated
advertising placement
• Adapt pricing (yield management)
• Promotion/recommendation
• Cross-selling
(Big) data empowers all key functions
Key business objectives:
• Sale of data
“Big data” helps everything from marketing, to
distribution, to planning.”
Matthew Eric Bassett, NBCUniversal
“(Data is) one of those things that as companies realize
the value, they will make it part of their core company
function so they can leverage it in the way that continues
to strengthen their position in the market.”
Juan Gorricho, Disney Theme Parks

4. • Recommendations algorithms
• Better informed decisions on production
• Automating video stories using Big Data technology
• Adapting the content to the context
Content: Promotion, acquisition, adaptation, automation
“We have a big team of people who are experts in programming, who see many, many different
pitches and read many, many different scripts. But then there’s definitely the data part of it as well,
where we enter different elements of proposals into our system, and it spits out a prediction as to ‘Will
Netflix members love this?’ and ‘How many people will love it?’”
Joris Evers, Netflix
“We’ll find clusters that show people who are interested in
Jennifer Lawrence are also interested in penguins”
Ky Harlin, BuzzFeed

5. Advertising: Make TV as accountable as digital
• Programmatic advertising,
where TV channels sells
qualified customers directly
to advertisers through
common sets of criteria.
• More information on TV viewers
• Addressable TVs
• Combination of media and
advertisers data
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“Data and technology will change the advertising business
in the next five years more than we've seen in the last 30
years”
Linda Yaccarino , NBCUniversal
• Automation
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6. • From unstructured to structured data:
• Unstructured data, including video, audio, email, research, social media feeds and more, which represent 80 percent
of all Big Data
• Storage and processing costs
• Costs decreasing but data volume increasing
• Data scientists
• Acquisition of external data
• Sky Media combines internal data from all the Sky platforms with purchases from Tesco’s 17 million Club card holders
• Retrieve data for Programme-related from social networks
• Geolocation data
• Etc.
Significant costs associated to big data
• Profile
• Content description
• Popularity
• Tastes
• Context
• Etc.
• Content producers
• Broadcasters
• Aggregators
• Distributors
• Users
• Device
• Web
• Market research
• Company
• Etc.
Data Data producers Data sources
Complexity
But big data implies complexity and costs
“Raw data is both an oxymoron and a bad idea; to the
contrary, data should be cooked with care.”
Geoffrey Bowker, University of California
“The challenge is taking the scale and size of data and
making achievable results”
Ranga Muvavarirwa, Time Warner Cable

7. • Need to cross data
• Need for scale
• Need to access web data
• Google, Facebook gathering TV-related data
Challenges for media companies
Data brokers ?
• Data brokers (e.g. Acxiom, Experian, Dunnhumby) entering the TV scene
Will media companies keep control of their data ?
“The things that Acxiom has always been good at – utilizing data to create better targeted marketing
campaigns – can now be applied to using data to create better experiences for people everywhere across any
device. Not just at their mailbox.”
Scott Howe, Acxiom