Eli Noam

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New Audience Research for New Media

Eli Noam Columbia University

Conference on Next Generation Audience Measurement

International Media Management Academic Association

Columbia University June 25

• Get pix of paul lazarsfeld, frank stanton

• John lavine, chris scholz • Phil napoli, bozena

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EN; CITI IMMAA.Phil Napoli Fordham Bozena, health. Corey Spencer Jason Buckweitz John Lavine------ Chris Scholz and his team

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• My own Role here is not just to welcome you, as much pleasure that gives me.

•  but to create a setting and context. Before the more specialized presentations are given 4

• NOT MY SUBJECT of research • BUT A TERRIFIC TOPIC. •  Suggested by John Lavine • And there are people here who make

this their life’s wok in academia or practice.

• But sometimes it is good to have a little distance, and to ask a few provocative questions upfront.

• And this I will do here. 5

Outline • 1. Why traditional audience

research is important and difficult • 2. Is there really a next-generation

audience research? Yes and No. •  3. Why next-generation audience

research helps create next-generation media problems

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Audience analysis is, of course, highly important

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•  every media firm – and we are not talking here just about TV type companies--wants to know – Who its potential buyers are – What their willingness to pay is – What their price sensitivity is

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– What product features they value – What they like about competing

products – How to identify market segments

and select target markets – Etc.

•  1. For media providers, to find out who the audience for a content is, and why.

•  2. For an advertiser, to find out who the audience for an advertising message is, what its effectiveness is, and why.

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•  3. To a social or behavioral scientist, to find out why people watch or listen to some content, and what the societal and cultural implications are.

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A. Audience Research is Methodologically Difficult

•  It’s easy to graph a hypothetical demand curve in a theoretical economics model

• But very hard in the real world to determine actual nature of audience demand, and the factors that go into it,

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“Assume a Demand Curve”

P

Q

But Where Exactly Is It? 14

Demand analysis is particularly important (and difficult) for media and information firms

1.  High Investment Needs Ahead of Demand

2.  High Uncertainty 3.  Instability of

Preferences

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4. “Public Good” characteristics

5.  Unstable Markets 6.  Rapid Tech Change 7.  Interdependent User

Demand (“Network Effects”, “Bandwagon effects”)

8. Strong cross-elasticities 9. Supply Creating its Own

Demand

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B. The stakes are high

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• A. It makes a big money difference.

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• Metering is not about technology, but about money

• Any change in metering procedure or in definitions has economic effects

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Example: Overall Effect of People Meters on Ratings

•  Permanently lowered overall TV ratings in 1990 by an average of about 4.5 points.

•  CBS: lost 2.0 points: NBC: showed avg. loss of 1.5 ABC: little effect 22

CBS Lost 2.0 Points in change to people meter

http://i.afterdawn.com/v3/news/cbs_logo.jpg

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NBC Lost 1.5 Points

http://www.midnightchimesproductions.com/MCP/images/NBC-logo.gif 24

Business Impact • In 1990, each ratings point was

worth approximately $140 million/yr

• Decrease in ratings therefore could cost major networks between $400 and $500 million/yr.

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• Cable: in contrast, ratings gain almost 20%.

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Effects on Programming Categories 15 Years Later • Participation shows were

boosted 5 points in rating; sitcoms 1.5; news 0.2:

• All other categories dropped. Medical shows showed highest drop; -4.1

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•  In NYC, Fox 5, UPN 9 and WB 11 showed big drops.

Similarly, an Impact of Local People Meters

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LPM Effects • Fox TV network and several local

stations complained that LPM undercounts minority viewers in cities.

• “Don’t Count Us Out”, a group funded by News Corp., generated political pressures in Washington and NYC on Nielsen. John Maynard, “Local People Meters May Mean Sweeping Changes on

TV,” The Washington Post, April 28, 2005, A01.

http://images.zap2it.com/20031016/fox_logo_240_001.jpg

• Thus one can see that ratings technology and ratings methodology affect dollars, Euros, and Yens

• It is therefore important that the ratings agencies are trusted by all sides

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Cultural stakes are high, too • Getting a program from GE-

Comcast’s NBC isnt the same as getting a GE toaster.

• Content makes a difference, and has a multiplier through network effects, and content with high numbers gets produced more readily than content with low numbers.

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• The “long tail” choices were not captured

• If you don’t measure it, it does not exist.

• Hence, they were ignored and under-served 31 32

C. The problem of accuracy:The

numbers can be erroneous, biased,

or manipulated 33 34

Japanese Rating Scandal • In 2003 a producer of the

Nippon TV Network (NTV) manipulated television ratings for his show

“Heads Roll in NTV Ratings Scandal.” Japan Times Online. 19 November 2003. Last accessed on 19 June 2007 at http://search.japantimes.co.jp/cgi-bin/nn20031119b6.html.

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Japanese Rating Scandal • The producer used money to find

out what specific household were being observed by the ratings agency Video Research Ltd. and got those homes to watch certain shows by bribing the occupants through various benefits.

“Heads Roll in NTV Ratings Scandal.” Japan Times Online. 19 November 2003. Last accessed on 19 June 2007 at htt p://search.japantimes.co.jp/cgi-bin/nn20031119b6.html.

• As a result of the scandal, the chairman of Nippon Television Network (NTV) Corporation was forced to resign

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Manipulating Book Best-Seller Lists

• Publishers or authors buy their own books in bulk from stores around the US to get their sales up for the NY Times list

Michael Tracy Fred Wiersema

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http://ecx.images-amazon.com/images/I/71Q44K6FSCL._SL500_.gif

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• Business consultants Michael Tracy and and Fred Wiersema, authors of The Discipline of Market Leaders, spent $250,000 to buy 10,000 copies of their own book, making it a Best-Seller. The book spent 15 weeks on the list.

• eventually sold over 250,000 copies.

http://battellemedia.com/archives/old%20book%206.gif 40

Mis-Reporting of Circulation Numbers

•  2004: Belo Corp. (Dallas Morning News and other papers, and 19 TV stations) – Investigation on false numbers – Counted unsold papers – Overstated circulation 5.1%, Sundays

11.9% • Refunds $23 Mil, loses advertiser

confidence

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Belo Corp.

http://cache.daylife.com/imageserve/07kf7XU5UEcuB/610x.jpg 42

Mis-Reporting of Circulation Numbers

• Other mis-reporting newspapers: – Hollinger (Chicago Sun-Times) – Tribune Co. (Newsday, Hoy, etc.)

– Counted unsold copies not returned

– Criminal investigation – Overstated 40,000 copies, Sunday, 60,000 copies

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43 http://sadbastards.files.wordpress.com/2006/11/sun-times-small.jpg 44 http://www.dyingwell.com/images/newsday.jpg

•  These manipulations were right under the nose of celebrated journalists who take pride in investigative journalism.

• But somehow they all missed those juicy stories.

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D. Audience Research is Operationally Difficult

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•  So let me remind you of major traditional methodologies

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Personal Interviews • In-home

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49 http://www.infonet.st-johns.nf.ca/providers/nhhp/newsletter/spring00/02_photo.gif

Personal Surveys

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Mail and Phone Surveys

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Focus Groups

Friedman, Motion Picture Marketing http://www.ctinfocus.com/images/foc.JPEG

52 http://www.funworldmagazine.com/2003/Jun03/Features/Larger_Than_Life/images/A13Screen.gif

Test Markets

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• So these were the groups who decided whether ET would die or get home

• Or whether glenn close would live or die in “Fatal Attraction”.

• And then there is my favorite, ---self-reporting of sales

• By newspapers… 54

Self-Reporting Audit Bureau of Circulation (ABC)

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• Or by book stores, such as for the best seller lists.

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Best Seller Lists

And then there are the film distributors with their weekly box office lists

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• And, of course, for television

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Paper Diaries

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• In these tedious and repetitive efforts, there was technology to assist, of course

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Automated and Real-

Time Metering

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Nielsen Audimeter, 1930s

Nielsen Instantaneous Audimeter, 1971

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Kiewit’s “hot bodies”

infrared sensor. But disturbed by the “Big Dog

Effect”

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More Practical Solution: The Nielsen People Meter

• Nielsen under pressure by competition AGB (UK)

• A meter rests on top of every TV in a Nielsen household and each family member has an assigned number.

•  It’s inconvenient to log in every time • A “passive” meter is more convenient.

John Maynard, “Local People Meters May Mean Sweeping Changes on TV,” The Washington Post, April 28, 2005, A01.

http://www.nielsenadvertiserservices.com/images/box_4.gif

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People Meter

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Passive Meters Carried by Consumers

• Arbitron Passive People Meter (PPM)

Source:ppm.arbitron.com 70

• Arbitron PPM (worn by users) is better able to keep up with – Multiple TV sets in household – Out-of home viewing

• But requires uses to wear the device or have it nearby

• more expensive, but can be used for radio, TV, Cable, and others.

Source: Broadcasting & Cable, 2/2002

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• Identifies audio and TV content through active codes embedded in the program itself and in the commercial messages

• Search engines identify the programs and the advertisements that are watched

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• This enables real time reports on watching or listening

• can meter broadcast, DBS, PVR, digital cable, and radio use.

http://nbc.com/Friends/index.html

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Cable Box

http://www.samsung.com/us/system/consumer/product/2008/05/09/smt_h3090twc/SMT-H3090_dimensien.jpg 74

– Columbus, Ohio pornography trial: “Captain Lust” was shown to be one of the most popular programs

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Most Popular Program in Columbus, Ohio

http://www.moviegoods.com/Assets/product_images/1010/213997.1010.A.jpg

Least Popular Program • Only 3 viewers: “You and the

Economy” (featuring 3 economics professors)

“You and the Economy” 78

•  CUBE data used in litigation and courts. – Columbus, Ohio pornography trial: “Captain Lust” was shown to be one of the most popular programs

– New Haven, CT: Least watched “You and the Economy” (A Panel of Yale economics professors was watched by 3 HHs)

•  Cable industry decided not to collect STB data, individually or in aggregate, to avoid giving customers a feeling they are being watched and monitored.

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•  But STB data is coming back • Some media research agencies

use aggregated STB data acquired from cable operators to provide a second by second-by-second analysis of viewing habits.

“MTV Networks Leverages Charter Data from TNS Media Research”, Wireless News, August 10, 2007

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TiVo Box

http://www.nytimes.com/images/blogs/tvdecoder/posts/1107/tivo-box.jpg

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Music Sales – POS System

http://www.savagebeast.com/images/best-buy-inlines.jpg 82

Nielsen Broadcast Data System (BDS)

• Used for the Billboard Top 100 Singles

• Tracks songs played on the radio http://www.covenantdesigns.com/marketing/top_100_9surf.jpg

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Broadcast Data System (BDS) •  tracks over 1,000,000 songs each

year. • Some songs are big on radio but

not in sales.

“About Nielsen BDS.” BDSonline.com. Last accessed on 15 June 2007 at http://www.bdsonline.com/about.html. 84

• Would increase sample size to hundreds of thousands per market

• Concept and technology introduced already in 1980s (CUBE cable system) in Columbus, Ohio

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TiVo Box

http://www.nytimes.com/images/blogs/tvdecoder/posts/1107/tivo-box.jpg

2011: Approximately 100,000 DirecTV households became part of the Nielsen’s local TV ratings after a deal with Kantar Media to collect STB viewing data in a number of markets.

http://www.fierceiptv.com/story/nielsen-use-kantars-directv-stb-data-ratings/2011-07-26

•  Leading U.S. advertising agencies and programmers signed on to use the DIRECTView (launched by TNS Media Research)

http://tvbythenumbers.zap2it.com/2009/01/28/tns-media-launches-audience-measurement-product-using-directv-set-top-box-data/11676/

•  Service includes ad occurrence data, top market breakouts, ability to set retention metrics to evaluate commercial avoidance, creative wear-out level and audience flow.

•  Stable, consistent ratings are provided for even small, digital and HD networks.

http://tvbythenumbers.zap2it.com/2009/01/28/tns-media-launches-audience-measurement-product-using-directv-set-top-box-data/11676/

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•  So we can observe that audience research is

• methodologically difficult •  economically important •  subject to attempts at manipulation,

and •  operationally difficult

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• And now, on top of it, we are getting all those new ways to deliver, and to use and consume

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Video Platforms—Old and New

• Broadcast TV • Cable •  Satellite

•  DVR •  VOD cable •  Wi-Fi and hotspot

wireless laptops and tablets

•  Smartphones cellular wireless

•  IPTV phone companies •  User-generated storage

—YouTube •  Online VOD Netflix,

Hulu, etc. 92

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2. Is there really a next-generation audience

research? Yes and No. • New tools

• New players • New methodologies?

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• A. New Tools

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Cookies

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Major Tool: Cookies •  Software that produces electronic files to tag

individual customers with a unique identification. – Allows a website to recognize an individual. – Allows an audience research firm to recognize

users – Similar to “people meter” approach – Combine user-centric and producer-centric

approaches Deck, Cary A., “Tracking Customer Search to Price Discriminate.” Electronic Inquiry, April 1, 2006.

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RFID Tracking of Media Products

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Mouse Activity • number of clicks • time spent moving the

mouse in milliseconds • time spent scrolling • time spent on website

or a particular webpage.

Mark Claypool, David Brown, Phong Le, and Makoto Waseda, “Inferring User Interest,” in IEEE Internet Computing, Vol. 5:6, November 2001, p. 35.

http://www.dalveydepot.com/DalveyBMS.jpg

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Click-Through (CTR) Software

• Measures whether user clicked on an ad to link to the advertiser

http://www.answers.com/main/content/wp/en/thumb/0/03/325px-Pop-up_ads.jpg 102

Inflated Click Rates

• Creating fake clicks • robot hits • This has become a big

problem • Fake clicks by people

has become a cottage industry in India http://ewic.bcs.org/images/robot.jpg

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Smart Face Recognition

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M- Research

M-research • Location-based research

– Can factor in location, proximity, time, with individual information, in real time,

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M-research • Location-based research

– Can factor in location, proximity, time, with individual information, in real time,

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107 Location-based Services

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Cellphone Use for Media Measurement

• Using apps on cell phones to measure what consumers listen to and see –  Provider: Integrated Media Measurement Inc

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109 Social Networking with Location

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Cellphone Use for Media Measurement

• Using apps on cell phones to measure what consumers listen to and see –  Provider: Integrated Media Measurement Inc

• Can measure out-of-home tv viewing

• Measure real-time effects of advertising

• Mobile couponing. differentiated pricing 111 112

Audience Perception Analyzers

• Linked to software and hardware that registers the responses and their intensity. INSTANT ANALYSIS TECHNOLOGY HELPS RATE COMMERCIALS

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Psycho-Physiology Data

• More generally, psycho-physiology sensors

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Heart Rate (HR)

Niklas Ravaha, “Contributions of Psychophysiology to Media Research: Review and Recommendations, ” MEDIA PSYCHOLOGY, Vol. 6 No. 2, 2004, pp. 193–235.

http://josephhall.org/images/bp_hrt.jpg

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Electroencephalographic (EEG) Activity

• Measures brainwaves using electrodes.

http://www.blackwellpublishing.com/abstract.asp?aid=161&iid=4&ref=0956-7976&vid=10

http://www.nexstim.com/images/prod_eeg_01.jpg

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Electrodermal Activity (EDA)

•  http://www.electrodermology.com/pics-new/biotronprobe-drop.jpg

•  Skin conductance of electricity increases when sweat increases due to arousal.

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Electrodermal Activity (EDA)

EDA measures of “before”, “during”, and “after” responses to an emotional picture and a calm picture

http://web.axelero.hu/lavender/kpt/hallgatokhoz/vassy/weboldal/H7KLFI1.JPG

Facial electromyography (EMG)

119 http://www.acoustics.org/press/159th/toth01.jpg

Respiratory sinus arrhythmia irregularity

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•  The logic of increasingly granual audience research and data is to drill down to the individual level.

•  This means, in practical terms, that the collection technology has to be individualized rather than based on location like a peoplemeter, or platform based.

•  And this probably means a device that people carry with them, probably a smartphone app of some sort that can identify media audio watermarks. 122

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• Demand measurement will be increasingly – real-time – global – large samples – Individualized – Matching of Advertising, Pricing, and Cons. Behavior

http://images.google.com/imgres?imgurl=http://210.75.208.159/eolympic/xbj/txtx/image/txtx.jpg

• Can measure out-of-home tv viewing

• Measure real-time effects of advertising

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B. New Players

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•  Kantar (UK, WPP) •  Ipsos (France) •  comScore (incl.

Media Metrix) •  Wakoopa •  Hitwise

•  TruMedia •  Quividi •  stickyPixel •  CognoVision •  Networked

Insights •  Visible Measures

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Overview Several companies have developed innovative cross-platform methodologies to produce putatively accurate numbers.

Nielsen •  Nielsen Media

Research--TV •  Nielsen/NetRatings—

Internet and Digital Media

•  Nielsn BuzzMetrics– consumer-generted media

•  Nielsen Consumer

•  Nielsen Online •  Nielsen Mobile •  Nielsen Business Media •  Nielsen Bookscan •  Nielsen Soundscan •  Nielsen Videoscan •  Marketing Analytics •  Nielsen Cinema •  etc

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Web Rating Companies

Source:Web rating: Heavy traffic ahead, The Industry Standard 9/18/00

(Nielsen)

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Methodology

• Sample randomly recruited by phone and mail. Sample of 50,000.

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Arbitron System

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• At the end of each day, the participant plugs the PPM into the “base station” which then transmits the data to the household data collection “hub” "The Portable People Meter

System." Arbitron.com. Arbitron, n.d. Web. 22 June 2012. <http://www.arbitron.com/portable_people_meters/thesystem_ppm.htm>.

•  Participants earn “points” for time meter was active throughout the day

•  Data from basestation is sent to “household hub” which sends data over telephone to arbitron

•  Hub has LCD screen for feedback and problem diagnosis

"The Portable People Meter System." Arbitron.com. Arbitron, n.d. Web. 22 June 2012. <http://www.arbitron.com/portable_people_meters/thesystem_ppm.htm>.

Audio Encoding •  Data is collected by

“psychoacoustic masking,” which is able to create a “fingerprint” which corresponds to a specific series of digits. From this, a code emerges that identifies the source of the signal.

•  "The Portable People Meter System." Arbitron.com. Arbitron, n.d. Web. 22 June 2012. <http://www.arbitron.com/portable_people_meters/thesystem_ppm.htm>.

PPM

"The Portable People Meter System." Arbitron.com. Arbitron, n.d. Web. 22 June 2012. <http://www.arbitron.com/portable_people_meters/thesystem_ppm.htm>.

Approaches • ComScore’s UDM (Unified Digital

Measurement) • Nielsen’s GTAM (Global Television

Audience Measurement) •  Intel’s (Cognovision) Anonymous

Video Analytics (AVA) • Adobe’s Omniture • Visible Measures’ VideoMetrics 138

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Comscore’s UDM Unified Digital Measurement integrates traditional third-party, panel-based audience measurement with client’s server-side data.

Abraham, Linda. “Unified Digital Measurement™: Not Just Another Pretty (Hybrid) Face.” comScore Voices. 31 May 2009. comScore. Last accessed on 21 June 2012 at http://blog.comscore.com/2010/04/unified_digital_measurement.html

UDM cont. Server data measures “total tonnage” of traffic in terms of unique cookies, while panel data provides insight on actual “consumer engagement and demographics.” UDM combines the two into a consistent, hybrid metric.

Abraham, Linda. “Unified Digital Measurement™: Not Just Another Pretty (Hybrid) Face.” comScore Voices. 31 May 2009. comScore. Last accessed on 21 June 2012 at http://blog.comscore.com/2010/04/unified_digital_measurement.html

UDM cont. The number of unique cookies and the actual number of unique viewers differ widely. In 2009, comScore measured 1.5 billion unique cookies in the U.S. compared to only 200 million unique internet users. Abraham, Linda. “Unified Digital Measurement™: Not Just Another Pretty (Hybrid) Face.” comScore Voices. 31 May 2009. comScore. Last accessed on 21 June 2012 at http://blog.comscore.com/2010/04/unified_digital_measurement.html

UDM cont. Internet audience members may be using multiple browsers on multiple machines in multiple locations. UDM is a metric that can account for such complications, since it uses data from comScore’s proprietary panel of 2 million people to weight and validate server data.

Abraham, Linda. “Unified Digital Measurement™: Not Just Another Pretty (Hybrid) Face.” comScore Voices. 31 May 2009. comScore. Last accessed on 21 June 2012 at http://blog.comscore.com/2010/04/unified_digital_measurement.html “COMSCORE ANNOUNCES MEDIA METRIX 360: THE NEXT GENERATION OF GLOBAL DIGITAL AUDIENCE MEASUREMENT.” comScore Press Releases. 31 May 2009. comScore. Last accessed on 21 June 2012 at http://www.comscore.com/Press_Events/Press_Releases/2009/5/comScore_Announced_Media_Metrix_360

UDM cont. comScore uses UDM to segment audience measures according to demographic, region and numerous other variables. They present their findings in traditional advertising terms, such as reach and frequency.

“COMSCORE ANNOUNCES MEDIA METRIX 360: THE NEXT GENERATION OF GLOBAL DIGITAL AUDIENCE MEASUREMENT.” comScore Press Releases. 31 May 2009. comScore. Last accessed on 21 June 2012 at http://www.comscore.com/Press_Events/Press_Releases/2009/5/comScore_Announced_Media_Metrix_360

UDM cont. comScore implements UDM in its Media Metrix Core Reports, which measure audiences in 41 individual countries and 6 global regions.

“Media Metrix Core Reports.” comScore Products and Services. comScore. Last accessed on 21 June 2012 at http://www.comscore.com/Products_Services/Product_Index/Media_Metrix_Suite/Media_Metrix_Core_Reports

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Nielsen’s Total Internet Audience (TIA)

TIA is very similar to the UDM, in that it uses audience panels to extrapolate an accurate metric from the otherwise unreliable information produced by cookies.

“Online Measurement.” Measurement. Nielson. Last accessed on 21 June 2012 at http://nielsen.com/us/en/measurement/online-measurement.html

TIA cont. Nielsen uses a proprietary method to recruit a panel of 500,000 internet users, with 200,000 in the U.S., then applies insights on their behavior in order to understand how content is consumed by different demographics “Online Measurement.” Measurement. Nielson. Last accessed on 21 June 2012 at http://nielsen.com/us/en/measurement/online-measurement.html

TIA cont. In this way, Nielson translates data from cookies into metrics like Reach, Frequency, and Gross Rating Points. In this form, market research can be accurately compared across traditional and new media channels. “Online Measurement.” Measurement. Nielson. Last accessed on 21 June 2012 at http://nielsen.com/us/en/measurement/online-measurement.html

TIA cont. Nielson researches media consumers in 100 countries around the world.

“About us.” Nielson. Last accessed on 21 June 2012 at http://www.nielsen.com/us/en/about-us.html

Nielson Cross Platform Measurement

In order to account for time-shifted and mobile media consumption, Nielson integrates data from their People Meter Panel and their Online panel.

“Cross Platform Measurement.” Measurement. Nielson. Last accessed on 22 June 2012 at: http://www.nielsen.com/us/en/measurement/cross-platform-measurement.html

Cross Platform Measurement cont.

Measures of mobile media consumption use census-style surveys complimented by data from on-device meters. These meters consist of software that runs silently in the background of phones and tablets, monitoring user activity.

“Cross Platform Measurement.” Measurement. Nielson. Last accessed on 22 June 2012 at: http://www.nielsen.com/us/en/measurement/cross-platform-measurement.html “Smartphone Study: FAQs and contacts.” Nielson. Last accessed on 22 June 2012 at: https://mobilepanel2.nielsen.com/nenroll/help.do?l=en_uk&pid=2

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Nielsen/Hulu •  Hulu/similar sites do not factor into Nielsen ratings: shows only qualify if they air 100% of the commercials from the television broadcast--Hulu/similar sites only carry 25% of these commercials

•  Fancast Xfinity online service and TV everywhere (Time Warner) qualify

•  Reiher, Andrea. "Nielsen to Add Online Viewing of TV Shows into Ratings Number."Zap2It.com. Zap2It, 24 Jan. 2012. Web. 22 June 2012. <http://blog.zap2it.com/frominsidethebox/2010/01/nielsen-to-add-online-viewing-of-tv-shows-into-ratings-number.html>.

Nielsen also plans to adopt a new, standardized system that will track television and online audiences across 16 world markets.

Nielsen’s Global Television Audience Metering (GTAM)

Mandese, Joe. “Nielsen Unveiling Suite Of Next-Generation TV Meters: Designed To Enhance Compliance, Cross-Platform Measurement Too.” 11 May 2012. MediaDailyNews. Last Accesed 5/22/2012 at http://www.mediapost.com/publications/article/174443/nielsen-unveiling-suite-of-next-generation-tv-mete.html?print

• More accessible for consumers and less “invasive” than Nielsen’s current methodology

• Hardware will not be physically connected to any household media devices (tv set, tuner)

• 2014 scheduled launch date Mandese, Joe. “Nielsen Unveiling Suite Of Next-Generation TV Meters: Designed To Enhance Compliance, Cross-Platform Measurement Too.” 11 May 2012. MediaDailyNews. Last Accesed 5/22/2012 at http://www.mediapost.com/publications/article/174443/nielsen-unveiling-suite-of-next-generation-tv-mete.html?print

GTAM Hardware Users place a plastic encased “code reader” within 6 feet of their TV speaker. It detects inaudible audio watermarks in programming and relays them back to Nielson via a cell-phone modem. Nielson plans to test the accuracy of this system against its current system in 4Q 2012. Nielsen Zornow, Dave. "Nielsen Chooses Plastic Over Paper For TV Ratings." Media News And Views, 2 June 2012. Web. Last accessed on 20 June 2012 at: http://www.medianewsandviews.com/2012/06/dz_nmr_gtam2012/

GTAM’s Watermarking Nielsen’s code reader detects imperceptible watermarks embedded in distributed content. These watermarks can withstand any kind of compression, which will assist in measuring video in wired and wireless platforms.


GTAM’s “Scrolling Text People Meter” • An LED screen instructs viewers

w/text to participate in the measurement process

• This will create more compliant panels, but, controversially, may also influence viewer behavior


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Visible Measures • An analytics company that

specializes in social video and uses two platforms for measuring: “Viral Reach Database” and “Video Metrics Engine”

• They produce three metrics: True Reach, Video Engagement, Brand Advocacy

"About Us." Visible Measures. N.p., n.d. Web. 21 June 2012. <http://corp.visiblemeasures.com/about-us>.

Visible Measures’ VideoMetrics Engine

-  “light weight, one time” integration w/the site’s video player

- Tracks every video everywhere the player travels online

- Measures every time viewer presses play, fast forward, or shares through email/social media


Visible Measures’ Metrics • True Reach: Measured by

combined Video Placements, Video Views, Sentiment Analysis (comments/rating scores) – Produces concise snapshot of 50 most common commenting terms


Metrics cont. • Video Engagement:

– Initial attention: % of viewer drop off at very beginning of video

– Average attention: average rate viewers abandon video

– Captivation: rate of rewinding to watch specific segments of video

"Optimize Your Video Inventory." Measure Audience Engagement with Internet Video. Visible Measures, n.d. Web. 21 June 2012. <http://corp.visiblemeasures.com//video-engagement>.

Visible Measures used to track video campaigns by:

• YouTube, •  ESPN, • Bing, • Yahoo, • AOL

• Fox •  Procter &

Gamble • Microsoft • Unilever • Ford Dello, Cotton. "Forgot Your User ID ?" Adage.com. Ad Age Digital, 22 Sept. 2011. Web. 22 June 2012. <http://adage.com/article/digital/visible-measures-raises-13-million/229965/>.

Visible Measures’ Supported Video Players

•  Adobe Flash •  HTML 5 Video •  Microsoft Silverlight (Netflix) •  Apple Quicktime •  DivX "Measuring Multiple Digital Video Delivery Technologies." Measure Online Video Advertising, Content, and Audiences. N.p., n.d. Web. 22 June 2012. <http://corp.visiblemeasures.com/supported-video-technology>.

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Google Analytics/Event Tracking Normally, Google Analytics only records when a page has been loaded. This does not address what happens/what the user does inside of that page. Therefore, embedded videos often get overlooked in standard analytic research. "Optimize Your Video Inventory." Measure Audience Engagement

with Internet Video. Visible Measures, n.d. Web. 21 June 2012. <http://corp.visiblemeasures.com//video-engagement>.

Event Tracking That said, sophisticated users of Google Analytics can use the “event tracking” feature and track code to reveal how often the video is watched and what users do when they watch it (FF/Pause/RW) Weber, Jonathan. "Video Tracking in Google Analytics." Video Tracking in Google Analytics: Introduction. LunaMetrics, 9 Nov. 2010. Web. 21 June 2012. <http://www.lunametrics.com/blog/2010/11/09/video-tracking-google-analytics-introduction/%20>.

Adobe Omniture • Uses “auto-track” function • Data loads automatically into

“SiteCatalyst” analytic feature • Tracks unique views, com-ple-

tion rates, time and per-cent viewed, con-ver-sion events, mile-stones reached, rev-enue con-tri-bu-tion,

Hartness, Brandon. “Tracking Video Consumption with SiteCatalyst and the new Flash 10.3 release.” Adobe Digital Marketing Blog. 3 June 2011. Adobe. Last accessed on 22 June 2012 at http://blogs.adobe.com/digitalmarketing/analytics/tracking-video-consumption-with-sitecatalyst-and-the-new-flash-103-release/

Omniture’s partnerships with online video players

• OSMF (Open Source Media Framework): an open video software framework designed for Adobe Flash

• Bright-cove: the leading online video hosting platform

Hartness, Brandon. “Tracking Video Consumption with SiteCatalyst and the new Flash 10.3 release.” Adobe Digital Marketing Blog. 3 June 2011. Adobe. Last accessed on 22 June 2012 at http://blogs.adobe.com/digitalmarketing/analytics/tracking-video-consumption-with-sitecatalyst-and-the-new-flash-103-release/

Omniture cont. Through Brightcove alone, Omniture provides audience measurement for the video players used by the New York Times Company, Discovery Communications, Sony BMG, Time, and the Washington Post. “Our Customers.” Bright Cove. Last accessed on 22 June 2012 at: http://www.brightcove.com/en/customers

Omniture, cont. Omniture’s client list spans 75 countries, and incudes eBay, AOL, Wal-Mart, Disney, Gannett, Microsoft, Neiman Marcus, Oracle, Countrywide Financial, General Motors, Sony and HP. “The Stevie Awards for Sales and Customer Service.” Awards. The Stevie Awards. Last accessed on: http://www.stevieawards.com/pubs/sales/awards/426_2435_17669.cfm

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Omniture and HBO GO HBO GO App sends its data to metrics.HBOGO.com. This data is then sent to an Omniture server—what viewers watch, what they browse, etc. The data comes in real-time to Omniture servers. Williams, Wes. "Review: Deep Dive Into HBO GO." Interactive TV Today. N.p., 11 June 2011. Web. 22 June 2012. <http://itvt.com/blog/review-deep-dive-hbo-go>.

CognoVision •  A Toronto based company,

bought by Intel in 2010 •  Uses Intel Audience Impression

Metrics Suite (AIM) •  Measures impressions, length of

impressions and gender using Anonymous Video Analytics

“Intel AIM suite.” Overview. Intel. Last accessed on 22 June 2012 at: http://intel.cognovision.com/intel-aim-suite

Cognovisions’ Anonymous Video Analytics (AVA)

• Detects patterns on people’s faces (using small cameras), but never saves images (in contrast to traditional biometric research)

• Pixel patterns determine how long something has been viewed, approximate age/gender

"CognoVision." Wikipedia. Wikimedia Foundation, 17 June 2012. Web. 21 June 2012. <http://en.wikipedia.org/wiki/CognoVision>.

How it works •  Sensors track how long the user

lingers or shifts his eyes from ad to ad

•  Cognovision then detects and compiles the data and “can even prompt the sign to change its message depending on the age or gender of the viewer.”

•  "Intel Buys Toronto Digital Signage Company." Signageinfo.com. N.p., 18 Nov. 2010. Web. 21 June 2012. <http://www.signageinfo.com/digital-signage/5251/intel-buys-toronto-digital-signage-company/>.

AVA Privacy Issues Often criticized as an invasion of privacy but Intel’s AVA is non-invasive since it only saves the patterns of faces, not the image of the face itself "CognoVision." Wikipedia. Wikimedia Foundation, 17 June 2012. Web. 21 June 2012. <http://en.wikipedia.org/wiki/CognoVision>.

•  InsightExpress provides digital marketing research to measure mobile consumer behavior.

http://mobilebeyond.net/u-s-smartphone-user-engagement-with-the-mobile-internet-joy-liuzzo-of-insightexpress/

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•  Integrated Media Measurement Inc (IMMI) recruited a panel of BlackBerry and iPhone users to use IMMI’s software on their Smartphones to observe and report their consumption of Olympics TV programming.

•  IMMI downloads software to cell phone users, which creates digital signatures of all audio media, and any online activities performed through the cell phone device and location information.

•  Data gathered from cell phones and computers is transmitted to IMMI’s central data base to determine viewing audiences, consumer behavior, and other trends.

http://www.atvcapital.com/atv-news/integrated-media-measurement-brings-proprietary-location-tracking-capability-to-media-measurement-pl

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New Methodologies?

178

• As mentioned, in the past, data collection methods were inaccurate, and slow.

• In parallel to these relatively leisurely collection methods, analytical tools were relatively time-insensitive. Lengthy studies, with methodologies that could not be done speedily. 179

•  I looked at the academic and articles, at what demand researchers do these days. And they still, judging from their citations or lack of citations, show little connectedness to other disciplines, or to corporate demand research.

180

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• Weak connection to academic marketing literature

• Weak connection to behavioral literature. Just a little with behavioral economics

181

• Weak connection with the real–world demand applications – the work that Nielsen or Simmons or the media research departments of networks do.

182

• Conversely, the type of work Nielsen and others do seems to be largely untouched by academic economics work.

• .

183

• And I wonder why this is so. • Because this should be the

golden age of demand research.

• Why? Because many of the constraints of the past, when it came to data, have been lifted.

184

• In fact, a lot of academic demand models could not ever be realistically applied.

• They included variables and information that were just not available.

185

• So what were these methodologies?

186

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Techniques of Data Analysis 1.  Statistical Inference 2.  Summary Audience Metrics 3.  Econometric Models 4.  Multi-equation Models 5.  Conjoint Analysis 6.  Diffusion Models 187

Empirical Methodologies

A. Econometric Modeling B. Conjoint Analysis C. Diffusion Models

188

Econometrics

189

• Usually with some variables for price, income, and socio-demographic control variables, maybe with prices of substitutes.

190

191

Conjoint Analysis

192

• Permits the researcher to identify the value (utility) that a consumer attaches to each product attribute

• There isnt much theory here, but at least it’s a workable methodology in the field.

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193

Example: Attribute-Importance Study For MP3 Player

(Scale 1-10) Attribute: Quality: 8.24 Styling: 6.11 Price: 2.67 User Friendliness: 7.84 Battery Life: 4.20 Customer Service: 5.66 194

• The value of a product is equal to the sum of the utility the consumers derive from all the attributes of the product.

P&B LLC DBA POPULUS http://www.populus.com/techpapers/conjoint.php

195

• This enables the researcher to predict the prices which the consumer would pay for a product of various combinations of attributes.

Thomas T. Nagle & Reed K. Holden, “The Strategy and Tactics of Pricing: A Guide to Profitable Decision Making,” Second Edition 1995

196

• There are computer packages (i.e. ACATM, Adaptive Conjoint Analysis) that generate an optimal set of trade-off questions and interprets results.

• But is it accurate? Or useful? • People hardly ever

decompose a product by its features

197 198

Diffusion Models

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199

Epidemic Diffusion Models

200

• “Epidemic model.” A “logistic” function y(t) = N{1+0 exp [-kt]}

201

Problems

• finding acceleration point • finding the “saturation level”

202

• comparison of the product to be forecast with some earlier product that is believed to have been similar

203

But now, things have changed on the data collection end. And it is the anlaytical end that is

the constraint

204

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Challenge #1 : Coordinating and

integrating these data flows

205 206

•  That is a practical issue. • Media audience research companies

are trying to integrate their data. • Nielsen, fore example.

–  Nielsen DigitalPlus integrates set top box data with People Meter data, transaction data from Nielsen Monitor Plus, Retail and scanning information from AC Nielsen, and modeling and forecasting information from several data bases (Claritas, Spectra and Bases.)

Katy Bachman, “Nielsen to Roll Out DigitalPlus”, Mediaweek.com, February 12, 2007

• Nielsen intends to add consumers’ activities on the internet, and mobile

• But, where is academic research, when it comes to such integration of such data streams?

• Or, of such real-time sources?

208

Challenge #2: Create Linkage to Behavioral Models

209

• No strong link to behavioral models and analysis (psych, sociological, behavioral economics)

210

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Challenge #3: Need bridge between academic textbook theory of consumer demand and practical empirical work

211

Challenge #4: Creation of New Research Methodologies

212

• Methodology of demand analysis has not kept up with greater speed and comprehensiveness of data collection

213 214

• Therefore, the more powerful data collection tools will push, mandate, and enable the next generation of analytical tool.

• This should be the golden age of demand research. Many of the constraints of the past have relaxed when it comes to data collection. Yet the methodologies of demand analysis have not grown at the same pace and are holding back our understanding and power of prediction.

• Thus, in the past, demand analysis was constrained by weak data and clunky analytical models. Recently, however, things have changed on the data collection end. Data has ceased to be the constraint that it once was as more advanced collection tools have emerged.

37

•  First, there are now increasing ways to measure peoples’ actual sensory perceptions to media content and to products more generally. “Psycho-physiology” techniques measure heart rate (HR), brainwaves (electroencephalographic activity, EEG), skin perspiration (electrodermal activity, EDA), muscle reaction (electromyography, EMG), and breathing regularity (respiratory sinus arrhythmia, RSA) (See Ravaha 2000; Nacke et al. 2010).

• These tools can be used in conjunction with audience perception analyzers, which are hand-held devices linked to software and hardware that registers peoples’ responses and their intensity.

• Second, the technology of consumer surveying has also improved enormously. There are systems of automated and real-time metering. Radio and television listening and channel-surfing can be followed in real-time. Measuring tools are carried by consumers, such as the Passive People Meter (PPM) (Arbitron 2011; Maynard 2005).

• The TiVo Box and the cable box allow for instant gathering of large amounts of data. Music sales are automatically logged and registered; geographic real-time data is collected for the use of the internet, mobile applications and transactions (Roberts 2006; Cooley et al. 2002).

• Mobile Research, or M- Research, uses data gathered from cell phones for media measurement and can link it to locations. Radio-frequency identification (RFID) chips can track product location (Weinstein 2005). Even more powerful is the matching of such data. Location, transaction, media consumption and personal information can be correlated in real-time (Lynch and Watt 1999).

• This allows, for example, the measurement in real-time of advertising effectiveness and content impact, and enables sophisticated pricing and program design.

• As one go forward, demand data measurement will be increasingly real-time, global, composed of much larger samples, yet simultaneously more individualized. This will allow for increasing accuracy in the matching of advertising, pricing and consumer behavior.

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• Of course, there are issues as data collection continues to improve (O’Leary 1999). The first challenge is the coordination and integration of these data flows (Clark 2006). This is a practical issue (Deck and Wilson 2006). Companies are working on solutions (Carter and Elliott 2009; Gordon 2007).

• Nielsen has launched a data service (Gorman 2009), Nielsen DigitalPlus, which integrates set top box data with People Meter data, transaction data from Nielsen Monitor Plus, retail and scanning information from AC Nielsen, and modeling and forecasting information from several databases (Claritas, Spectra, and Bases.) Nielsen intends to add consumers’ activities on the internet and mobile devices into this mass of data.

• The second challenge is that of privacy: the power of data collection has grown to an extent that it is widely perceived to be an intrusive threat (Clifton 2011; Matatov et al. 2010; Noam 1995). So there will be legal constraints on data collection, use, matching, retention and discrimination.

•  The third problem is that when it comes to the use of these rich data streams, academic and analytical research are falling behind. When one looks at what economists in demand research do these days, judging from the articles’ citations, they still show little connectedness to other disciplines or to corporate demand research (Holbrook et al. 1986, Weinberg and Weiss 1986).

• There is a weak appreciation of the literatures of academic marketing studies, of information science on data mining (Cooley 2002), of the behavioral sciences (Ravaha et al. 2008), of communications research (Zillman 1988; Vorderer et al. 2004), and even in the recent work by behavioral economists (Camerer 2004).

• There is little connection to real–world demand applications – the work that Nielsen or Simmons or the media research departments of networks do (Coffey 2001). Conversely, the work process of Nielsen and similar companies seems to be largely untouched by the work of academic economists, which is damning to both sides.

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• The next challenge is therefore to create linkage of economic and behavioral data. Right now there is no strong link of economic behavioral models and analysis. Behavioral economics is in its infancy (Kahneman 2003, 2012), and it relies mostly on individualized, traditional, slowpoke data methods of surveys and experiments.

• The physiologists’ sensor-based data techniques, mentioned above, have yet to find a home in economic models or applied studies. There is also a need to bridge the academic world of textbook theory of consumer demand with the practical empirical work of media researchers.

• Thus, the biggest challenge in moving demand studies forward is the creation of new research methodologies. The more powerful data collection tools will push, require and enable the next generation of analytical tools.

• One should expect a renaissance in demand analysis. Until it arrives one should expect frustration.

233





234

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•  1. Privacy •  2. Cost •  3.Segmentation

235

A. Privacy •  Ultimately one moves towards identifying the

individual’s media behavior •  Either by observation, with permission or

without, or by very detailed inference. – ‘you cant tell a dog on the internet? With

enough data points of behavior, can pretty much determine that you’re a poodle

236

•  This obviously has privacy implications. – that’s obvious, and everybody says

that

237

•  It’s a thin line that separates attentive service from stalking

• And there is a big difference between first-party data collection and use, by the party with whom the media user knowingly has a transaction

•  In contrast to third-party use, by reselling the information to others, who then use it for marketing and other purposes 238

•  Some regulation is unavoidably coming or already here in some regions.

•  Those who think that this will go away and people get used to it are deluding themselves.

239

•  I’ve been writing about privacy in electronic media since 1986.

•  European style regulatory agencies do not work well in this environment

•  Self regulation has problems, because it pays to break out of it.

• Market forces have a real place, but they need laws on transparency and on opt-in consumer choice. 240

41

B. Cost • Advertising will be more targeted •  Less waste. Therefore more effective.

But it’s an illusion to believe that this is going to save advertisers any money.

•  The reason is, that it will be more effective for everybody. So one should expect an arms race of targeted ads to overcome one’s competitors.

241

•  So this is like a xxx war, where each side tries to outdo the other.

•  Fancier messages, price offers, maneuverings for search engine optimization, and other costly efforts.

• But for narrower and narrower slices of people.

242

• And since in crude mass advertising, the tradtional mass media had a cost advantage, and first mover advantage, the main advantage of online media is that they provide individualization and interactivity

243

• Creates incentives for ‘search optimization’– affects content

244

• All this will generate a media system that is much more expensive to operate than that of thte past.

• But at the same time, more fragmented

• And in a competitive environment, also low revenue

245

C. Segmentation

246

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•  Initially, the mass nature of TV and the clunky technology made measurement to be in the nature of mass, aggregate, HH, maybe with some very rough demographic categories.

247

• Also, targeting means stereotyping. Low income consumers will get ads that reinforce their status.

•  Pricing will be individualized

248

• Must deliver groups with sufficient granularity

249

• Price offers can be made dependent on such user behavior indicating high or low price sensibility.

250

• advertising on the web and other new media is essential to their health, but it also requires audience research.

251

•  Privacy issue would exist if one could identify the individual

•  Suppose one could fully anonymize---

• And suppose one could not surmise the individual by all the info tags like address and other unique data and data constellations------would there be then still a problem?

252

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• Ads individualized • Content also individualized • Interactivity also gets

character, by video games providing choices in behavior

253

•  Social media research enables identifcation of influecial taste makes, and they would get bombarded.

254

• Other consumers are identified as low income, and they get ads for fast food and for diet programs.

255

• Media are partly integrative in nature, partly particularist in nautre

•  The technology now makes them more particularist.

256

• But now, the technology and its economic implications create a fragmented audience. Russ Newman. Turow.

• Granularity coming down to the individual dimension

257

• On the level of consumption, advertising, and marketing, this means that people will be easily differentiable

•  They will get different advertisng messages for different products, and different price offers

258

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•  Poor people will get fast food ads, and dieting ads.

• Rich people will get ads stroking their social superiority

•  I now get ads, whenever I go to Pandora, trying to sell me a retirement village.

•  If they do this often and long, I get the message that I really should do this. 259

• Will also lead to political campaigns that fragment people into groups and fragment politics

• Even more interest group oriented.

• Aggregators of sub-groups. 260

• Now people will be served their news, and select them, based on narrow criteria of preference and status.

261

•  People more and more talking to themselves

•  One reason for current bad state of politics.

•  Brief period in which media were widely shared, 1950s-70s.

•  Few newspapers, mostly one per city, plus 3 centrist TV networks headquartered within a few blocks.

•  The technology created a nationwide, society-wide audience

262

•  Internet enthsiasts usually give credit to almost everything good to the internet.

•  So why not also the bad?

263

•  Internet enthusiasts celebrate, rightly, the culture of collaboration and connection. Social media. Collective innovation.

• But what about dis-connection? • As one connects in new ways, one

also disconnects some of the old ways. There is only so much time. 264

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265

Conclusion •  I’ve come to the end •  I have argued that the new forms of

audience research encourage, inevitably, trends of societal centrifugalism, and that they are also adding to the cost of marketing.

266

•  I have argued that we have moved from data shortage to data glut, that tools are being developed and refined and integrated.

• But that the main problem is how to analyzed the data effectively and rapidly.

267

•  It is here that social and behavioral scientists need to make progress

• And it is here that media audience practitioners and media academic researchers must collaborate

• And my hope is, that this workshop here is a step in that direction

268

The End

• Thank you, audience • Best wishes, IMMAA • [email protected]

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