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W E L C O M E T O T H E
EVOLUTION OF V IDEO C O M M U N I T Y
C E N T R I S M A R K E T I N G S C I E N C E
2 ©Centris | Proprietary & Confidential
The Evolution of Video Community: Introduction
OVERVIEW
• Since 2010, Centris has fielded an ABS-driven survey known as the Evolution of Video. The survey reports on consumer trends as they relate to OTT, pay-TV, broadband, wireless use, etc.
• The Evolution of Video Survey draws from 30,000 respondents each quarter and can be used for predictive models and consumer trends.
• In 2013, Centris began development of The Evolution of Video Community (EOVC) is a multi-modal, nationwide research
initiative designed to examine shifting consumer behaviors related to video, wireless, and broadband service. • In addition to the survey, the components include:
– A survey panel of more than 2,000 prequalified respondents
– Proprietary, multi-modal, in-home passive data collection software installed on phones, tablets, computers, etc.
– Multi-platform Facebook survey tool
– Bill submission: Community members submit their voice, video, and data bills – Integration and overlays with other Centris data sources
3 ©Centris | Proprietary & Confidential
The Evolution of Video Community: Introduction
APPROACH
• The EOVC combines multiple methodologies to collect from a panel of hundreds of US households – Participants receive software to download on their household devices (laptop, iOS, Android, etc.)
– Centris also delivers a branded router companion
– Incentives vary by level of participation
KEY OUTPUT
• Device inventory of the home and detailed usage patterns (clickstream behavior, video viewing, etc.) that takes place on
the home network and out-of-home on devices that carry the software
• EOVC draws all behavior, with the exception of transaction behavior, but including ad interaction and ad avoidance
• Centris works with major US universities for refined research PRIVACY • No personal or identifiable information is collected
• CASRO code of ethics observed
• Centris uses multiple, secure data storage solutions to guard against hacking or data theft
• Data discarded monthly
BRANDED NETWORK BASED ROUTER COMPANION
• Deployment of pre-configured router to perform
network sweeps
• Complete control of device inventory (timing, frequency)
• Gathers game consoles, smart devices and all in-home usage of software
• Protects user from malware
CENTRIS SOFTWARE • Reset browser on each device to point to a
central web proxy
• Captures URL detail and easy configuration
• Follows mobile devices outside of home network
• Devices are limited to computers, laptops, smartphones and tablets
• Global deployment
4 ©Centris | Proprietary & Confidential
Collection Engine
Combines two approaches to capture Internet traffic data on network:
© 2 0 1 5 | P R O P R I E T A R Y & C O N F I D E N T I A L
C E N T R I S M A R K E T I N G S C I E N C E
ANALYSIS & REPORTING: DIFFERENT APPROACHES TO COLLECTION
© 2 0 1 5 | P R O P R I E T A R Y & C O N F I D E N T I A L
C E N T R I S M A R K E T I N G S C I E N C E
CENTRAL PROXY
© 2 0 1 5 | P R O P R I E T A R Y & C O N F I D E N T I A L
C E N T R I S M A R K E T I N G S C I E N C E
PATHWAY CASE STUDY
EOVC DATA COLLECTION • EOVC tracks user online behavior across time, geography, websites, platforms and devices • Users provide demographic and device information in surveys, then install software and hardware that collect their
online activity
BENEFITS OF EOVC ANALYSIS • Rich data on browsing pathways
– Multi-branch pathways with device and demographic information – Pathway analysis makes possible real-time PREDICTION of future clicks and advertising segmentation
• Popularity measure of entertainment websites and content
– Score popularity of TV and video content, as well as implications for piracy and revenue – Popularity drives advertising and targeting decisions
INP
UT
User demographics User assessment of Internet habits Clickstream activity Device information Time & geography A
NA
LY
SIS
Pathway ordering Pathway branching Pathway folding
Pathway composition Pathway variables Metrics of popularity on specific platforms
AC
TIO
N
Habit recognition Prediction of video streaming Prediction of ad clicking Segmentation by device OTT-focused analysis
10 ©Centris | Proprietary & Confidential
The Evolution of Video Community Collection & Analysis
11 ©Centris | Proprietary & Confidential
User 1 : Male – July 7 2014
S O C I A L M E D I A TWITTER
M S N FOX SPORTS
NBA ARTICLES
S E A R C H E S BING SEARCH
P R O F E S S I O N A L PC WORLD
ARTICLE
C A R E E R INTERVIEW,
PENGUIN Q&As
C A R E E R MONSTER
CAREER ADVICE
F O O D Seagrasecapes.
com/flavors
S E A R C H E S GOOGLE SEARCH
F O O D EHOW:
HOW TO GRILL CHICKEN
Ads
Ads
12 ©Centris | Proprietary & Confidential
User 2: Male – July 2 2014
R E T A I L AMAZON
S O C I A L M E D I A FACEBOOK
N E W S YAHOO INSIDER
S P O R T S SPORTS YAHOO,
BLOGS
S P O R T S SPORTS YAHOO,
VIDEO
S P O R T S SPORTS YAHOO,
BLOGS
R E T A I L COUPONS
N E W S TWC CENTRAL
Ads
Ads
USER 1
DEVICES HEAVY USER FREQUENT USER MODERATE USER LOW USER
iPhone
iPad
Laptop
USER 2
DEVICES HEAVY USER FREQUENT USER MODERATE USER LOW USER
iPhone
iPad
laptop
Blu-ray
DVR
13 ©Centris | Proprietary & Confidential
User Analyses
14 ©Centris | Proprietary & Confidential
Case Study: Pathway Including Clicks on MTV
User simultaneously streaming video and browsing social media converges on MTV. 1
After browsing/streaming MTV content, user moves to information sites that lead to shopping on Amazon. 2
Video Streaming GoogleVideo.com
12:05 AM
Video Streaming YouTube.com
12:14 AM
Social Media – Professional
LinkedIn.com 12:10 AM
Social Media Facebook.com
12:18 AM Link to MTV.com
Media Content MTV.com 12:19 AM
Article: Robin William’s death
Media Directory TVGuide.com
12:23 AM
Media Content CBS.com 12:23 AM
Video Streaming Hulu.com 12:24 AM
Video Streaming YouTube.com
12:24 AM Media Content
SonyPictures.com 12:19 AM
Social Media Facebook.com
12:37 AM
Encyclopedia Wikipedia.org
12:42 AM
Media Database IMDB.com 12:42 AM
Media Content MTV.com 12:36 AM
E-Commerce Amazon.com
12:43 AM
15 ©CENTRIS | PROPRIETARY & CONFIDENTIAL
Example Pathway #1
6:45 AM 6:46 AM 6:47 AM 7:04 AM 7:08 AM 7:13 AM 7:31 AM 7:35 AM 7:36 AM
Login.Live.com (Email)
Xbox.com (Video
Games)
BBC.co.uk (News & Media)
Facebook.com (Social
Network)
StubHub.com (Shopping/
Sports)
Google.com (Search Engine)
Twitter.com (Social
Network)
Google.com (Search Engine)
Amazon.com (General
Merchandise)
K E Y T A K E A W A Y S 1. User reaches XXX from BBC News 2. User multi-tasks between his PC and Windows Phone (where he has a game on) 3. XXX a likely motivator for user’s later shopping sports tickets
I M P L I C A T I O N S • This pathway shows that user could come to XXX from a variety of devices as well as websites • Pathway underlies strong relationship between sports consumption and purchasing decisions
Windows PC
Windows Phone
1
2
3
• Saturday August 23, 2014 • Male • 35–44 Years Old • 1 Member in the Household
*WINDOWS PC INITIATED
*WINDOWS PHONE
INITIATED
XX.go.com Ticket ad
served
XX.go.com (Sports)
Conversion
7:01 AM 7:07 AM
16 ©CENTRIS | PROPRIETARY & CONFIDENTIAL
Example Pathway #2: Multiple Household Devices
5:29 PM 6:39 PM 6:40 PM 6:54 PM 9:25 PM 10:11 PM 10:13 PM 10:14 PM 10:15 PM
Destiny (Video Games)
XXgo.com (Sports)
XX.go.com (Sports – Soccer)
Sports.MSN.
com (Sports)
SoccerCorner.com (Shopping –
Sports)
Netflix.com (TV & Video)
Instagram.com (Social Network)
Refinery29. com
(Fashion & Modeling)
PinkIsTheNewBlog.com
(Celebrities & Entertainment
News)
Glamour.com (Magazines &
E-Zines)
Xbox
Apple TV
Macintosh PC
iPhone
1
2
3
*iPHONE INITIATED
*APPLE TV INITIATED
*XBOX INITIATED
*SAMSUNG SMART TV INITIATED
*MACINTOSH PC INITIATED
K E Y T A K E A W A Y S 1. User’s household spends its Friday night employing multiple devices. Content on
one device often triggers browsing on another device. 2. The XXX soccer content on Apple TV leads to shopping for sports equipment on
the iPhone. 3. There is correlation between XXX and streaming Netflix content later in the night.
• Friday September 12, 2014 • Male • 25-34 Years Old • Other Members in the
Household Include: Female, 25–34; Male, 6–9
“Network A”
TV & Video
File Sharing
Arts & Entertainment
Photography
Social Media
Shopping
General Merchandise
News & Media
Search Engine
Video Games
Clothing
17 ©CENTRIS | PROPRIETARY & CONFIDENTIAL
Walmart.com
Binodal Pathways from “Network A” to Walmart
Shopping
Reference
Banking
Search Engine
12%
21%
18%
15%
14%
32%
14%
11%
29%
17%
8%
18% 7%
13%
10%
12%
24%
18%
16%
26%
6%
14%
5%
25%
32%
18%
15%
34%
There are high conversion likelihoods from video-related sites, which can ultimately lead to e-commerce. 1
Consumers of “Network A”
content have a good likelihood
of banking online, which could lead to shopping on
Walmart.com.
2
• ONLINE SEARCH 10:20PM
• SOCIAL MEDIA • FACEBOOK 10:22PM
• ONLINE DATING 10:27PM
• SURVEY PANEL 10:45PM
• JOB SEARCH 11:08PM
• VIDEO STREAMING 12:05AM
• FACEBOOK WITH MTV CONTENT 12:18AM
• MTV & OTHER MEDIA CONTENT 12:19AM
• SHOPPING 12:43AM
USER DEMOGRAPHICS • Gender: Male
• Location: Bay City, Texas
• Age Group: 25-34
• Living Situation: Single
• Race: Caucasian
• Devices Owned:
– Android Smartphone – Desktop Computer – Roku
• Time on Video Streaming: 20 hours/week
• History of Video Streaming: Constant Levels
BROWSING SESSION INFORMATION
• Timeline: 8/17/14 10:20PM – 8/18/14 1:03AM
• Devices: Desktop Computer with Windows OS
18 ©Centris | Proprietary & Confidential
Case Study: Demographics & Pathway Study
18%
82%
PERCENT OF TOTAL USERS THAT VIEW SPORTS
View Sports
Don't View Sports
33%
67%
SPORTS VIEWER GENDER
Female
Male
28%
72%
WEBSITES USED TO WATCH SPORTS
yahoo
msn.fox
31%
69%
SPORTS VIEWER AGE RANGE
25-34
35-44
19 ©Centris | Proprietary & Confidential
User Analyses
20 ©Centris | Proprietary & Confidential
Collection, Storage & Maintenance
• Data is captured through multiple sources and delivered to a combination of secure cloud and Centris servers – No PII is captured
• One household generates gigabytes of data in one day, so storage and data cleansing is a major factor in this effort
– Centris has developed a proprietary filtering and scrubbing algorithm to capture and refine data for analysis
• Centris stores the data in a combination of secure, internal servers and cloud solutions
– Raw historical data is collapsed for long term storage
• Centris can pull daily, weekly or monthly reports, minimizing needs for large storage and ensuring security
21 ©Centris | Proprietary & Confidential
Contacts
Let’s Get Social - Follow CentrisMarSci
STEVE ENNEN President
OFFICE: 267.558.3176
CELL: 646.334.5893
JOCELYN BAYLE Senior Director ,
Business Development
OFFICE: 267.558.3179
CELL: 917.232.8364
MICHAEL GUAN Manager,
Statistics & Innovation
OFFICE: 267.558.3192
CELL: 917.280.0123