ROLE OF BIG DATA IN INTERACTIVE MEDIA

S. Ghanbari

DATA IN MEDIA…

106

Megabyte

Gigabyte

109

1012

Terabyte

500 TB of new data are ingested in FB DB

1018 Exabyte

1EB of data is created on the internet each day

= 250 million DVDs 1015

Petabyte

1021

Zettabyte

1.3 ZB of network traffic by 2016

1024 Yottabyte

Todays Digital Universe

=250 Trillion DVDs

1027

Brontobyte

Tomorrows Universe

NEW METRICS…

HOW MUCH DATA

2016:

44

Zettabytes

Flood of Big Data

1 Billion Viewers

-500Hours a Minute

40Million

Wikipedia Pages

in 288 different languages

1.79 Billion FB Users

-350 Million Photos Uploaded each day

-250 Billion Photos Uploaded - 60billion FB messages sent daily

-4 new petabytes of data per day

316 Million Twitter Users

-300 Billion Tweets shared Total number of photos

shared on Instagram: 34 B

Broadband speeds will nearly double by 2020.

The number of devices connected to IP networks will be more than three times the global population by 2020:

7 billion connected people will be using an estimated 30 billion devices.

Consumer video-on-demand (VoD) traffic will nearly double by 2020.

FUTURE DATA USAGE TRENDS

COMPETITION = MORE DATA PRODUCTION

DEFINITION 3V – 5V – 7V

1. VOLUME

2. VELOCITY

3. VARIETY

4. VARIABILITY

5. VERACITY

6. VISUALISATION

7. VALUE

Data at rest is a snapshot of the information that is collected and stored, ready to be analyzed for decision-making. For example, a video camera can collect 1.75 terabytes (TB) of data per day or 2.52 petabytes (PB) per year.

Processed by inexpensive systems: many “smart analytics” systems available to process this data, including IBM BigInsights

Data in motion is the process of analyzing data on the fly without storing it.

Example: a theme park that uses wristbands to collect data about their guests. These wristbands would constantly record data about the guest’s activities, and the park could use this information to personalize the guest visit with special surprises or suggested activities based on their behavior

“DATA AT REST” & “DATA IN MOTION”

CMOS FEEL UNDERPREPARED FOR THE DELUGE OF DATA AND THE GROWTH IN SOCIAL MEDIA; THE PACE OF CHANGE IS TOO FAST

Preparedness for the data explosion

71%

2013 2011

82%

29% 18%

68%

2013 2011

66%

32% 34%

Preparedness for social media

Prepared Underprepared

Source: 2014 IBM IBV Global C-Suite Study

CMOs – Chief Marketing officers

POPULARITY

BIG DATA LANDSCAPE

BIG DATA LANDSCAPE 2016!!

HIGH-LEVEL DESIGN

Consumers with technologies that reach targeted people at optimal times in optimal locations. The ultimate aim is to serve, or convey, a message or content that is (statistically speaking) in line with the consumer's mindset.

Targeting of consumers (for advertising by marketers)

Data-capture

Data journalism: publishers and journalists use big data tools to provide unique and innovative insights and infographics.

BIG DATA IN MEDIA

NETFLIX Subscribers: 86.7 million in over 190

countries

Hours per day:125 million

Number of hours Netflix users watched in 2015: 42.5 billion hours

"75% of what people watch is from some sort of recommendation"

Data should be accessible, easy to discover, and easy to process for everyone.

Whether your dataset is large or small, being able to visualize it makes it easier to explain.

The longer you take to find the data, the less valuable it becomes.

Netflix content distributor content creator

DVD Mailing Business: 2006: Netflix Prize : 1 million dollars for best algorithm for predicting how its

consumers would rate a movie based on their previous ratings Limited by lack of customer information:

Customer ID, Movie ID, Rating, Date

Streaming business model: New data: time of day, time spent selecting movies, how often playback was

stopped (either by the user or network limitations) Tagging: paying customers to watch a movie and then suggest movies

taggers receive a 36-page training document 76,897 genres

Producing Popular Series: House of Cards (Director + Leading Actor) – 2 seasons with 26 episodes At a cost of $4

million to $6 million an episode, this 2-season over $100 million. Netflix made 10 different cuts of the trailer for House of Cards, each geared toward different

audiences. The trailer you saw was based on your previous viewing behavior. 3 Million New users – almost paid Netflix back for the cost of House of Cards.

NETFLIX: HISTORY OF ANALYTICS

When consumer pauses, rewinds, or fast forwards

What day they watch content (Netflix has found people watch TV shows during the week and movies during the weekend.)

The date content watched

What time content was watched

Where it was watched (post code)

What device was used to watch it (Eg TV for movies, tablets for kids programs, …)

When consumer pauses and leaves content (and if you ever come back)

The ratings given (about 4 million per day)

Searches (about 3 million per day)

Browsing and scrolling behavior

Netflix also looks at data within movies. They take various “screen shots” to look at “in the moment” characteristics. Netflix has confirmed they know when the credits start rolling; but there’s far more to it than just that. Some have figured these characteristics may be the volume, colors, and scenery that help Netflix find out what users like.

NETFLIX: TYPE OF DATA KEPT

Why does Netflix want to know when the credits roll? They probably want to see what users do afterward. Do they leave the app or go back to browsing?

Because if users leave the app after watching a show, that may mean they are more likely to cancel. Allow me to explain:

Through their analytics, Netflix may know how much content users need to watch in order to be less likely to cancel. For instance, maybe they know “If we can get each user to watch at least 15 hours of content each month, they are 75% less likely to cancel. If they drop below 5 hours, there is a 95% chance they will cancel.”

So now that they have this data, they can ask themselves “How do we help users watch at least 15 hours of content per month?” One idea: enable post-play, which automatically plays the next episode of a TV show

unless the user opts out. For movies, show movie suggestions (based on the rating of the movie just watched)

right after the credits start rolling and allow users to press play right from that screen.

TV Series X, Netflix is able to see (on a large scale) the “completion rate” (for lack of a better term) of users

“How many users who started TV Series X (from season 1) finished it to the end of season 3?” Then they get an answer. Let’s say it’s 70%.

Then they ask “Where was the common cut off point for users?

What did the other 30% of users do?

How big of a ‘time gap’ was there between when consumers watched one episode and when they watched the next?

IF TV Series had been cancelled THEN with 70% Restart/Recommission

TYPE OF QUESTIONS ASKED

NETFLIX ORGANIGRAPH

Employees: 3700 (800 developers)

Cloud and Platform Engineering

Consumer Insights

Content

Content Delivery

Content Operations

Content Platform Engineering

Customer Service

Data Engineering & Analytics

Finance

Financial Planning and Analysis

Human Resources

IT Operations

Legal

Marketing

Media Engineering and Partnerships

Partner Devices

PR

Product Creative

Product Engineering

Product Management

Science and Algorithms

Streaming Client

UI Engineering

User Experience

Flashback: a compilation of posts and photos that received the most “likes” or comments, all set to somewhat nostalgic background music

Photo Magic: Facial Recognition: what’s in it, what color is it, where was it taken, who is in it, are the people pulling a happy or sad face, etc.

FACEBOOK: NEW LEVEL BIG DATA

interact directly with those viewers based on our understanding of their interests and behaviours

Data strategy means Channel 4 has over 11 million registered viewers including over half of all 16 to 24-year-olds

CHANNEL4 ALL4

3 million data - Customers give (or refuse) their consent for Sky to use this data when they first subscribe.

Adsmart: This allows advertisers to show different commercials to homes watching the same television programme using 940 attributes: channel switching reduces by 33% over the ad break –

2015, Sky AdVance: This allows advertisers to deliver multi-platform campaigns across different screens, so that audiences see the right ad at the right time, in the right sequence and on the right screen.

Data visualisation tools: Agencies and advertisers will be able to press a button and see how their campaigns are performing.’

SKY

ANALYSIS CHALLENGES: COPYRIGHT + PRIVACY

27

ANALYSIS CHALLENGES: ….

28

MEDIA ANALYSIS CHALLENGES: NOISY CONTENT

In a TV context, big data is the digital trail left by viewers as they flick from channel to channel. This information is invaluable for broadcasters and advertisers alike: it reveals the audience’s likes and dislikes and allows broadcasters to target their content more accurately. However, when it comes to informing the creative process, it is still in its infancy.

We tend to talk about ‘insight’ now, rather than ‘big data’,” said Sky Media Deputy Managing Director Jamie West.

“Data can help you to understand what audiences are doing,” continued Chittick, providing “insight into consumption and behaviours”. She argued that “average video consumption per user per session” was a key measurement. “You want that to go up because you want to build loyalty and video viewership.”

Big data, though, reveals more than viewers’ TV consumption; it also provides information on their willingness to pay for content and stick with ads, rather than changing channels during commercial breaks.

Using data in TV is not a new phenomenon, said Douglas, pointing out that TV shows had long been commissioned, recommissioned or chopped on the basis of audience research. What had changed, he suggested, was that now “there’s an awful lot more data and [broadcasters] can do more with it”.

‘big data is changing media consumption – clients are spending less money but are prepared to pay higher prices for the media they buy because they can individually control how much value every single impression or TV ad spot [offers].’

While collecting and producing data are the first steps in the development of a Big Data practice, the acts of analysing and making the data actionable are the new mantras for media companies

In order to reach the wisdom stage, media companies need to embrace the opportunities from a Big Data strategy, invest in technologies and training in order to leverage the investment, and finally, use this newfound wisdom to improve processes such as customer service and products.

SUMMARY: BIG DATA IS CHANGING MEDIA CONSUMPTION

THANK YOU

“Information is the Oil of the 21 Century & Analytics is the Combustion Engine”

P. Sondergaard (Gartner Research)

“Hiding within the mounds of data is knowledge that could change the life of a patient or change the world”

A. Butte (Stanford School of Medicine)

“Processed data is information. Processed information is

knowledge Processed knowledge is Wisdom.”

(Ankala V. Subbarao)