|
Internet Advertising / Online Advertising Revenue 2000 - 2008
|
|
|
Top 50 Companies % share of total online advertising revenues in 2007
|
|
|
% of 2007 Full-Year Online Advertising Revenues by Pricing Model
|
|
|
% of 2006 Full-Year Online Advertising Revenues by Pricing Model
|
|
|
% of 2007 Fourth-Quarter Online Advertising Revenues by Pricing Model
|
|
|
% of 2006 Fourth-Quarter Online Advertising Revenues by Pricing Model
|
|
|
U.S. Advertising Market / Media Comparisons in 2007
|
|
|
US Online Social Network Advertising Spending (2008 - 2013)
|
|
|
US Total Online Advertising Spending (2008 - 2013)
|
|
|
US Online Social Network Advertising Spending (2008 - 2013) as a % of Total Online Advertising Spending
|
|
|
MySpace % share of all US social networking ad spend in 2008
|
|
|
Facebook % share of all US social networking ad spend in 2008
|
|
|
Widgets and applications % share of the total US social networking ad spending in 2008.
|
|
|
MySpace forecasted revenue in 2009
|
|
|
Facebook forecasted revenue in 2009
|
|
|
Widgets and applications forecasted ad revenue in 2009
|
|
|
US Child and Teen Internet Users, 2007 - 2012
|
|
|
US Child and Teen Internet Users % of Total Population, 2007 - 2012
|
|
|
% of Teens / Children that will go online at least once a month in 2009
|
|
|
Children and teens % of the total US Internet user population.
|
|
|
US Internet Users by Age, 2008
|
|
|
US Internet Users by Age as a % of Total Users, 2008
|
|
|
US Active Internet Users by Age July 2008
|
|
|
% of active Internet users in July 2008 that were children under age 18.
|
|
|
Number of households with next generation video game consoles in 2012
|
|
|
% of expected 2012 households with next generation consoles that are connected to the Internet
|
|
|
% of connected 2012 video game consoles that will use console-based video services at least once a week
|
|
|
The costliest natural disaster ever to hit the US
|
|
|
Number of deaths caused by Hurricane Katrina
|
|
|
Total amount of monetary damage caused by Hurricane Katrina
|
|
|
Number of deaths caused by Hurricane Katrina
|
|
|
Number of evacuees as a result of Hurricane Katrina
|
|
|
Number of homeless people in the US
|
|
|
Demographic make-up of the homeless population
|
|
|
Racial breakdown of homeless population
|
|
|
Average Income for a homeless individual
|
|
|
% of homeless that do not get enough to eat versus the average poor American adult
|
|
|
% of homeless that did paid work during the past month
|
|
|
% of homeless that have problems with alcohol, drug abuse, or mental illness
|
|
|
% of homeless persons that have been sexually assaulted
|
|
|
% of homeless that have been homeless for more than two (2) years
|
|
|
Number or people and children who experience homelessness in a given year
|
|
|
% of homeless population under the age of 18 and under the age of five (5)
|
|
|
% of homeless population that are women
|
|
|
% of homeless women that are unaccompanied / have no partner
|
|
|
% of homeless women claim to have been abused within the past year.
|
|
|
% of homeless women who claim domestic abuse as the reason for their homelessness
|
|
|
% of homeless population that are families with children
|
|
|
Ratio of homeless persons that have a severe or persistent mental illness
|
|
|
% of homeless population that are Veterans / Vets
|
|
|
% of homeless persons nationwide that are employed
|
|
|
Estimates of homeless persons per night and per Year in the US
|
|
|
Number of Americans who now live in hunger or on the edge of hunger.
|
|
|
Ratio of people in a soup kitchen line who are children
|
|
|
Number of American children who were hungry or at risk of hunger in 1999.
|
|
|
Largest and fastest growing segment of the homeless population.
|
|
|
Number of families who are lodging nightly in city shelters in New York City .
|
|
|
In 2000, increase in requests for emergency food assistance from families with children.
|
|
|
Number of children in the U.S. who live in poverty. The U.S. child poverty rate is higher than that of most other industrialized nations.
|
|
|
In 1999, number of all food stamp recipients who were children.
|
|
|
Number of children in the U.S. who live in working poor families.
|
|
|
The homeless population racial break-down / make-up in 1998.
|
|
|
% of cities surveyed by the U.S. Conference of Mayors that identified domestic violence as a primary cause of homelessness
|
|
|
% of homeless men who have served in the armed forces.
|
|
|
% of the single adult homeless population that suffers from some form of severe and persistent mental illness.
|
|
|
% of homeless persons who have mental illness that require institutionalization.
|
|
|
Worldwide Music Industry Revenues (2006 - 2011)
|
|
|
Worldwide Recorded Music Revenues (2006 - 2011)
|
|
|
Worldwide Music Publishing Revenues (2006 - 2011)
|
|
|
Worldwide Live Music / Concert Revenues (2006 - 2011)
|
|
|
North American Recorded Music Revenues (2006 - 2011)
|
|
|
North American Music Publishing Revenues (2006 - 2011)
|
|
|
North American Live Music / Concert Revenues (2006 - 2011)
|
|
|
North American Music Industry Revenues (2006 - 2011)
|
|
|
US Digital Music Revenues (2006 - 2011)
|
|
|
Worldwide Digital Music Revenues (2006 - 2011)
|
|
|
Worldwide Recording Industry Revenues from Mobile (2006 - 2011)
|
|
|
Worldwide Recording Industry Revenues from Online (2006 - 2011)
|
|
|
Worldwide Recording Industry Revenues from Physical (2006 - 2011)
|
|
|
US Recording Industry Revenues from Mobile (2006 - 2011)
|
|
|
US Recording Industry Revenues from Online (2006 - 2011)
|
|
|
US Recording Industry Revenues from Physical (2006 - 2011)
|
|
|
Music Revenues in North American in 2005
|
|
|
Music Revenues in Western Europe in 2005
|
|
|
Music Revenues in North American in 2010
|
|
|
Music Revenues in Western Europe in 2010
|
|
|
% of US Adult Music Listeners toward a 99-cent Price per Digital Download of a Song, January 2006 (% of respondents) - Too Expensive
|
|
|
Services that US Online Households Use to Download Music from the Internet, (% of respondents*)
|
|
|
Worldwide Music-Enabled Phone Shipments (2007)
|
|
|
Worldwide Music-Enabled Mobile Phone Sales,(millions of units)
|
|
|
Concert Ticket Revenues in North America (2001 - 2006)
|
|
|
Worldwide Concert Ticket Revenues, (billions)
|
|
|
European Music Executives" Who Believe Ending Digital Rights Management (DRM) Would Boost Download Sales, December 2006 - January 2007 (% of respondents)
|
|
|
European Music Executives' Opinions Regarding Digital Rights Management (DRM), December 2006 - January 2007 (% of respondents)
|
|
|
US MP3 Player Retail Sales, by Brand, February 2007 (% market share)
|
|
|
US Household Penetration of Select Stand-Alone Consumer Electronics and Converged Mobile Devices, Q4 2005 (% of households)
|
|
|
US Household Penetration of Select Stand-Alone Consumer Electronics and Converged Mobile Devices, Q1 2007 (% of households)
|
|
|
Ringtone Mobile Music Revenues in Europe (2011)
|
|
|
Full Track Mobile Music Revenues in Europe (2011)
|
|
|
Market Share of Mobile Music Revenues Worldwide, by Segment, 2006
|
|
|
Market Share of Mobile Music Revenues Worldwide, by Segment, 2011
|
|
|
Worldwide Revenues from Over-The-Air (OTA)* Full-Track Song Downloads, 2004, 2005 & 2011 (millions)
|
|
|
Worldwide Mobile Music Revenues, by Type, 2005
|
|
|
Worldwide Mobile Music Revenues, by Type, 2010
|
|
|
Music Sponsorship Spending in North America, 2003-2011
|
|
|
US Recording Industry Revenues, 2001-2006
|
|
|
US Music Performance Revenues, 2006-2011
|
|
|
American Society of Composers, Authors and Publishers (ASCAP) US Revenues, 2003-2006
|
|
|
Broadcast Music Inc. (BMI) US Revenues, 2003-2006
|
|
|
Worldwide Synchronization Licensing Revenues, 2006-2011
|
|
|
US Weekly Digital Media Users, XM Satellite Radio, 2005-2020
|
|
|
US Weekly Digital Media Users, Sirius Satellite Radio, 2005-2020
|
|
|
US Weekly Digital Media Users, Internet Radio*, 2005-2020
|
|
|
US Weekly Digital Media Users, Wireless Internet**, 2005-2020
|
|
|
US Weekly Digital Media Users, Mobile Phone Audio Streaming, 2005-2020
|
|
|
US Weekly Digital Media Users, HD Radio (terrestrial), 2005-2020
|
|
|
US Weekly Digital Media Users, Terrestrial Radio (cumulative), 2005-2020
|
|
|
US Weekly Digital Media Users, Internet Simulcast Terrestrial, 2005-2020
|
|
|
US Weekly Digital Media Users, Podcasting, 2005-2020
|
|
|
Money spent on pornography every second
|
|
|
Number of Internet users viewing pornography every second
|
|
|
Number of Internet users typing adult search terms into search engines
|
|
|
Frequency of new pornographic videos being made in the United States
|
|
|
2006 Worldwide Pornography Revenues by Country
|
|
|
2006 Worldwide Pornography Revenues per Capita
|
|
|
2006 Worldwide Pornography Revenues
|
|
|
2005 US Pornography Revenue by Type
|
|
|
2005 United States - US Pornography Revenues
|
|
|
2006 US Pornography Revenue by Type
|
|
|
2006 United States - US Pornography Revenues
|
|
|
Number of Pornographic websites
|
|
|
Number of Pornographic pages
|
|
|
Daily pornographic search engine requests
|
|
|
Daily pornographic emails
|
|
|
% of Internet users who view porn
|
|
|
% of Internet users who Received unwanted exposure to sexual material
|
|
|
Average daily pornographic emails/user
|
|
|
Monthly Pornographic downloads (Peer-to-peer)
|
|
|
Daily Gnutella "child pornography" requests
|
|
|
Number of websites offering illegal child pornography
|
|
|
Number of Sexual solicitations of youth made in chat rooms
|
|
|
Number of youths who received sexual solicitation
|
|
|
Worldwide visitors to pornographic web sites
|
|
|
Internet Pornography Sales
|
|
|
Average age of first Internet exposure to pornography
|
|
|
Age Group of the largest consumer of Internet pornography
|
|
|
% of 15-17 year olds having multiple hard-core exposures
|
|
|
% of 8-16 year olds having viewed porn online
|
|
|
% of 7-17 year olds who would freely give out home address
|
|
|
% of 7-17 year olds who would freely give out email address
|
|
|
Number of children's character names linked to thousands of porn links
|
|
|
% of Men admitting to accessing pornography at work
|
|
|
US adults who regularly visit Internet pornography websites
|
|
|
% of Promise Keeper men who viewed pornography in last week
|
|
|
% of Christians who said pornography is a major problem in the home
|
|
|
% of Adults admitting to Internet sexual addiction
|
|
|
Breakdown of male/female visitors to pornography sites
|
|
|
% of Women keeping their cyber activities secret
|
|
|
% of Women struggling with pornography addiction
|
|
|
Ratio of women to men favoring chat rooms
|
|
|
Percentage of visitors to adult websites who are women
|
|
|
Number of women accessing adult websites each month
|
|
|
% of Women admitting to accessing pornography at work
|
|
|
2006 Top Adult Search Requests
|
|
|
Demographic Breakdown of Sex Related Search Terms
|
|
|
Top Worldwide Search Requests for the term "Porn"
|
|
|
Top US City Search Requests for the term "Porn"
|
|
|
Top Worldwide Search Requests for the term "XXX"
|
|
|
Top US City Search Requests for the term "XXX"
|
|
|
Top Worldwide Search Requests for the term "Sex"
|
|
|
Top US City Search Requests for the term "Sex"
|
|
|
Number of Pornographic Webpages by Country
|
|
|
US Adult Video Sales and Rental Units
|
|
|
US Adult Video Sales and Rental Units
|
|
|
US Hardcore Pornography Titles Released
|
|
|
US Internet Users (2000 - 2003)
|
|
|
US Internet Users (2004 - 2005, 2007, 2008)
|
|
|
US Population (2000 - 2008)
|
|
|
Greenland Internet Users (2000, 2003, 2006, 2008)
|
|
|
Greenland Population (2000, 2003, 2006, 2008)
|
|
|
Saint Pierre et Miquelon Population (2000, 2006, 2008)
|
|
|
Canada Internet Users (2000, 2008)
|
|
|
Canada Internet Users (2003, 2005)
|
|
|
Canada Population (2000, 2003, 2005, 2008)
|
|
|
Bermuda Internet Users (2000, 2005, 2006, 2008)
|
|
|
Bermuda Internet Users (2003)
|
|
|
Bermuda Population (2000, 2003, 2005-2006, 2008)
|
|
|
Albania Internet Users (2000, 2002, 2006, 2007)
|
|
|
Albania Population (2000, 2002, 2006, 2007)
|
|
|
Andorra Internet Users (2000, 2006-2007)
|
|
|
Andorra Internet Users (2002)
|
|
|
Andorra Population (2000,2002, 2006-2007)
|
|
|
Austria Internet Users (2000, 2004)
|
|
|
Austria Internet Users (2008)
|
|
|
Austria Population (2000, 2004, 2008)
|
|
|
Belarus Internet Users (2000, 2003, 2005, 2007)
|
|
|
Belarus Population (2000, 2003, 2005, 2007)
|
|
|
Belgium Internet Users (2000)
|
|
|
Belgium Internet Users (2004)
|
|
|
Belgium Internet Users (2006)
|
|
|
Belgium Population (2000, 2004, 2006)
|
|
|
Bosnia Herzegovina Internet Users (2000, 2002, 2006, 2007)
|
|
|
Bosnia Herzegovina Population (2000, 2002, 2006, 2007)
|
|
|
Bulgaria Internet Users (2000, 2004, 2006)
|
|
|
Bulgaria Population (2000, 2004, 2006)
|
|
|
Croatia Internet Users (2000, 2004, 2006)
|
|
|
Croatia Population (2000, 2004, 2006)
|
|
|
Cyprus Internet Users (2000, 2004, 2007)
|
|
|
Cyprus Population (2000, 2004, 2007)
|
|
|
Czech Republic Internet Users (2000, 2003, 2006)
|
|
|
Czech Population (2000, 2003, 2006)
|
|
|
Estonia Internet Users (2000, 2006, 2007)
|
|
|
Estonia Internet Users (2004)
|
|
|
Estonia population (2000, 2004, 2006, 2007)
|
|
|
Faroe Islands Internet Users (2000, 2002, 2005, 2007)
|
|
|
Faroe Population (2000, 2002, 2005, 2007)
|
|
|
Finland Internet Users (2000, 2004, 2006)
|
|
|
Finland Population (2000, 2004, 2006)
|
|
|
France Internet Users (2000)
|
|
|
France Internet Users (2004, 2006-2008)
|
|
|
France Population (2000, 2004, 2006-2008)
|
|
|
Germany Internet Users (2000)
|
|
|
Germany Internet Users (2004, 2005, 2007)
|
|
|
Germany Population (2000, 2004, 2005, 2007)
|
|
|
Gibraltar Internet Users (2000), (2002)
|
|
|
Gibraltar Population (2000, 2002, 2006)
|
|
|
Greece Internet Users (2000, 2006)
|
|
|
Greece Population (2000, 2006)
|
|
|
Guernsey and Alderney Internet Users (2000, 2002, 2006)
|
|
|
Guernsey and Alderney Population (2000, 2002, 2006)
|
|
|
Hungary Internet Users (2000, 2007)
|
|
|
Hungary Population (2000, 2007)
|
|
|
Iceland Internet Users (2000, 2003, 2005-2006)
|
|
|
Iceland Population (2000, 2003, 2005-2006)
|
|
|
Ireland Internet Users (2000)
|
|
|
Ireland Internet Users (2002)
|
|
|
Ireland Internet Users (2008)
|
|
|
Ireland Population (2000, 2002, 2008)
|
|
|
Italy Internet Users (2000, 2004)
|
|
|
Italy Internet Users (2008)
|
|
|
Italy Population (2000, 2004, 2008)
|
|
|
Jersey Internet Users (2000, 2002, 2006)
|
|
|
Jersey Population (2000, 2002, 2006)
|
|
|
Latvia Internet Users (2000, 2003, 2005-2007)
|
|
|
Latvia Population (2000, 2003, 2005-2007)
|
|
|
Liechtenstein Internet Users (2000, 2002, 2006)
|
|
|
Liechtenstein Population (2000, 2002, 2006)
|
|
|
Lithuania Internet Users (2000, 2004-2006)
|
|
|
Lithuania Population (2000, 2004-2006)
|
|
|
Luxembourg Internet Users (2000, 2003, 2006-2007)
|
|
|
Luxembourg Population (2000, 2003, 2006-2007)
|
|
|
Macedonia Internet Users (2000, 2002)
|
|
|
Macedonia Internet Users (2006)
|
|
|
Macedonia Population (2000, 2002, 2006)
|
|
|
Malta Internet Users (2000, 2004, 2006)
|
|
|
Malta Population (2000, 2004, 2006)
|
|
|
Moldova Internet Users (2000, 2004, 2006)
|
|
|
Moldova Population (2000, 2004, 2006)
|
|
|
Montenegro Internet Users (2006)
|
|
|
Montenegro Population (2006)
|
|
|
Netherlands Internet Users (2000, 2003, 2006-2007)
|
|
|
Netherlands Population (2000, 2003, 2006-2007)
|
|
|
Norway Internet Users (2000, 2005, 2007)
|
|
|
Norway Population (2000, 2005, 2007)
|
|
|
Poland Internet Users (2000, 2005, 2007)
|
|
|
Poland Population (2000, 2005, 2007)
|
|
|
Portugal Internet Users (2000)
|
|
|
Portugal Internet Users (2004)
|
|
|
Portugal Internet Users (2006)
|
|
|
Portugal Internet Users (2007)
|
|
|
Portugal Population (2000, 2004, 2006, 2007)
|
|
|
Romania Internet Users (2000, 2004, 2006-2007)
|
|
|
Romania Population (2000, 2004, 2006-2007)
|
|
|
Russia Internet Users (2000, 2007)
|
|
|
Russia Population (2000, 2007)
|
|
|
San Marino Internet Users (2000, 2002, 2006)
|
|
|
San Marino Population (2000, 2002, 2006)
|
|
|
Serbia Internet Users (2006)
|
|
|
Serbia Population (2006)
|
|
|
Slovakia Internet Users (2000, 2004-2006)
|
|
|
Slovakia Population (2000, 2004-2006)
|
|
|
Slovenia Internet Users (2000, 2004-2007)
|
|
|
Slovenia Population (2000, 2004-2007)
|
|
|
Spain Internet Users (2000, 2004, 2006, 2007)
|
|
|
Spain Population (2000, 2004, 2006, 2007)
|
|
|
Sweden Internet users (2000, 2004, 2005, 2007)
|
|
|
Sweden Population (2000, 2004, 2005, 2007)
|
|
|
Switzerland Internet Users (2000, 2004-2006)
|
|
|
Switzerland Population (2000, 2004-2006)
|
|
|
Turkey Internet Users (2000, 2004)
|
|
|
Turkey Internet Users (2006)
|
|
|
Turkey Population (2000, 2004, 2006)
|
|
|
Ukraine Internet Users (2000)
|
|
|
Ukraine Internet Users (2006)
|
|
|
Ukraine Population (2000, 2006)
|
|
|
UK Internet Users (2005, 2007)
|
|
|
UK Internet Users (2000)
|
|
|
UK Population (2000, 2005, 2007)
|
|
|
Vatican City Internet Users (2000, 2002, 2006)
|
|
|
Vatican City Population (2000, 2002, 2006)
|
|
|
Trade Value of US Digital Music Sales in 2008
|
|
|
Digital Music % of 2008 Total Music Sales
|
|
|
Global Digital Revenue by Industry in 2008
|
|
|
Total music consumption (both licensed and unlicensed) from 2003 - 2007
|
|
|
Overall sales in the US hit an all time high in 2008, with music purchases across all formats
|
|
|
Number of tracks are downloaded without payment to rights holders (illegally downloaded) in 2008.
|
|
|
International music company digital revenues in 2008.
|
|
|
Global single track downloads in 2008
|
|
|
Top selling digital singles / downloads of 2008
|
|
|
US share of global digital music sales in 2008
|
|
|
% of Fashion Designers who are self-employed
|
|
|
Locations / Stats with the highest concentrations of fashion designers
|
|
|
Number of Fashion designer jobs held in 2006
|
|
|
% of fashion designers worked for apparel, piece goods, and notions merchant wholesalers;
|
|
|
Projected number of fashion designer jobs in 2016
|
|
|
Median annual earnings for salaried fashion designers in May 2006
|
|
|
Median annual earnings for the middle 50 percent of salaried fashion designers in May 2006
|
|
|
Median annual earnings for the lowest 10 percent of fashion designers
|
|
|
Number of online videos viewed by US Internet Users in December 2008
|
|
|
Top U.S. video property and number of videos served in December 2008
|
|
|
Number of online videos served by Fox Interactive in December 2008
|
|
|
Number of online videos served by Yahoo! Sites in December 2008
|
|
|
Number of online videos served by Viacom Digital in December 2008
|
|
|
Number of online videos served by Hulu in December 2008
|
|
|
% / percent of the total U.S. Internet audience viewed online video in December 2008.
|
|
|
Time spent watching online videos in December 2008
|
|
|
Number of viewers watching videos on YouTube in December 2008
|
|
|
Number of viewers watching videos on MySpace in December 2008
|
|
|
The duration of the average online video in December 2008
|
|
|
The duration of the average online video viewed at Hulu in December 2008
|
|
|
US Retail E-Commerce Holiday Season Sales 2003-2008
|
|
|
US Retail E-Commerce Holiday Season % change 2003-2008
|
|
|
US Holiday Season Retail Sales Growth 1998-2008
|
|
|
Percent of Annual US Retail E-Commerce Sales Attributed to the Holiday Shopping Season (2003-2008)
|
|
|
US Online Video Advertising Spending, 2007-2013
|
|
|
US Online Video Advertising Spending Growth 2008-2013
|
|
|
US Online Advertising Spending Growth by Video, 2008-2013
|
|
|
US Online Advertising Spending Growth by Sponsorships, 2008-2013
|
|
|
US Online Advertising Spending Growth by Search, 2008-2013
|
|
|
US Online Advertising Spending Growth by Lead Generation, 2008-2013
|
|
|
US Online Advertising Spending Growth by Classifieds, 2008-2013
|
|
|
US Online Advertising Spending Growth by Rich media, 2008-2013
|
|
|
US Online Advertising Spending Growth by E-mail, 2008-2013
|
|
|
US Online Advertising Spending Growth by Display ads, 2008-2013
|
|
|
US Online Advertising Spending Growth by Total, 2008-2013
|
|
|
US Online Leisure/Unmanaged Business Travel Sales (2007-2012)
|
|
|
US Online Leisure/Unmanaged Business Travel % changed (2007-2012)
|
|
|
US B2C E-Commerce Sales, 2007-2012
|
|
|
US Behaviorally Targeted Online Ad Spending (2006-2012)
|
|
|
US Behaviorally Targeted Online Ad Spending Growth (2006-2012)
|
|
|
US Behaviorally Targeted % total online display ad spending (2006-2012)
|
|
|
US Behaviorally Targeted % total online ad spending (2006-2012)
|
|
|
US Retail E-Commerce Sales, 2007-2012
|
|
|
US Retail E-Commerce percent change, 2007-2012
|
|
|
US Online Shoppers (2007-2012)
|
|
|
US Internet users (2007-2012)
|
|
|
US Online Buyers (2007-2012)
|
|
|
US Percent of Internet users (2007-2012)
|
|
|
Average Annual Amount US Online Buyers Spend Online (2007-2012)
|
|
|
Percent of Average Annual Amount US Online Buyers Spend Online (2007-2012)
|
|
|
US-User Generated Content Consumers, 2007-2012
|
|
|
US % of internet users 2007-2012
|
|
|
US-User Generated Content Creators, 2007-2012
|
|
|
US % of internet users 2007-2012
|
|
|
US-User Generated Content Advertising Spending, 2007-2012
|
|
|
Percent of online ad spending 2007-2012
|
|
|
US Online Social Network Advertising Spending 2006-2011
|
|
|
US Total Online Advertising Spending 2006-2011
|
|
|
US % of Total Online Social Network Advertising Spending 2006-2011
|
|
|
US Mobile Message Advertising 2007-2012
|
|
|
US Mobile Display Advertising 2007-2012
|
|
|
US Mobile Search Advertising 2007-2012
|
|
|
Mobile Message Advertising Worldwide 2007-2012
|
|
|
Mobile Display Advertising Worldwide 2007-2012
|
|
|
Mobile Search Advertising Worldwide 2007-2012
|
|
|
US Web Widget and Application Advertising Spending 2007 & 2008
|
|
|
Percent of total social network ad spending
|
|
|
Top 10 Web Widget Audiences in the US, Ranked by Unique Viewers, November 2007
|
|
|
% of total internet users who visit top social networking websites in November 2007
|
|
|
US Online Advertising Spending by Sponsorships, 2006-2011
|
|
|
US Online Advertising Spending by Search, 2006-2011
|
|
|
US Online Advertising Spending by Lead Generation, 2006-2011
|
|
|
US Online Advertising Spending by Classifieds, 2006-2011
|
|
|
US Online Advertising Spending by Rich media, 2006-2011
|
|
|
US Online Advertising Spending by E-mail, 2006-2011
|
|
|
US Online Advertising Spending by Display ads, 2006-2011
|
|
|
US Search Advertising Spending 2001-2011
|
|
|
US Online Percent Change in Social Network Advertising Spending 2007-2011
|
|
|
US Online Social Network Advertising Spending by Type of Network (MySpace) 2007 & 2008
|
|
|
US Online Social Network Advertising Spending by Type of Network (Facebook) 2007 & 2008
|
|
|
US Online Social Network Advertising Spending by Type of Network (Niche Social Networks and marketer -sponsored social networks) 2007 & 2008
|
|
|
US Online Social Network Advertising Spending by Type of Network (Other general social network sites and portal-based social networks) 2007 & 2008
|
|
|
US vs. Rest of World Online Social Network Advertising Spending 2007 & 2011
|
|
|
Share of Social Network Advertising Revenues, Niche and marketer-sponsored sites
|
|
|
Share of Social Network Advertising Revenues, MySpace
|
|
|
Share of Social Network Advertising Revenues, Facebook
|
|
|
Share of Social Network Advertising Revenues, Other
|
|
|
Number of mobile game downloaders during the second quarter of 2008
|
|
|
Top 3 mobile game titles by revenue
|
|
|
Most popular mobile game genres
|
|
|
Number of mobile phone subscribers globally
|
|
|
Number of text messages (SMS) sent worldwide each month
|
|
|
Number of single track downloads in the US (2008)
|
|
|
Number of digital album sold in 2008
|
|
|
% of total album sales made up by digital albums in 2008
|
|
|
First label to report the majority of its revenue now coming from digital channels
|
|
|
Number of mobile singles sold in Japan in 2008
|
|
|
Country with the biggest increase in digital sales in the first half of 2008
|
|
|
Number of single tracks downloaded in the UK in 2008
|
|
|
Number of digital album sales in the UK in 2008
|
|
|
Number of online single tracks downloaded in France in 2008
|
|
|
Number of digital albums sold in France in 2008
|
|
|
Number of tracks downloaded in France in 2007
|
|
|
Number of single track downloads in 2008 in Germany
|
|
|
Number of digital album sales in Germany in 2008
|
|
|
% of recorded music sales in the US accounted for by digital music in the first half of 2008
|
|
|
The proportion of US consumers’ disposable income spent on digital music vs. Europe
|
|
|
Online, US broadband users music spend compared to the UK and Spain (2007).
|
|
|
Top 5 Digital Markets / Countries
|
|
|
Number of music tracks sold internationally in 2008.
|
|
|
Number of tracks sold by Apple's iTunes since launch / inception (January 2009)
|
|
|
Largest music retailer in the US (February 2008)
|
|
|
Number of tracks, TV episodes, and films offered by iTunes
|
|
|
Number of tracks offered by Amazon MP3
|
|
|
% of Amazon MP3's customers who previously bought from iTunes
|
|
|
Demographic breakdown of Amazon MP3 customers vs. iTunes
|
|
|
Number of streams and playlists created at MySpace Music in the first month
|
|
|
% of active Internet users watching a video clip online in 2008
|
|
|
Number of consumer willing to view advertisements as the price of listening to music
|
|
|
Size of the global games industry in 2008 and 2012
|
|
|
% of all game sales made up by music games in the first half of 2008
|
|
|
Sales of the original Guitar Hero across all platforms in less than three years
|
|
|
Song sales through Xbox Live (includes downloads from Guitar Hero and Rock Band)
|
|
|
Size of the global / worldwide radio industry
|
|
|
% of consumers in the UK that say music encourages them to stay in stores longer
|
|
|
Size of the radio industry
|
|
|
Number of satellite radio subscribers
|
|
|
% of advertising in Canada attributed to music
|
|
|
Value placed on music by nightclub patrons as part of their nights experience
|
|
|
The fair price of using unprotected sound recordings at nightclubs
|
|
|
World's second largest digital music market
|
|
|
% of digital music sales attributed to mobile in Japan
|
|
|
% of mobile revenues in Japan that is attributed to full-length downloads to mobile
|
|
|
% of recorded music sales in Brazil that are attributed to digital music sales
|
|
|
% of digital music sales attributed to mobile channels in Brazil
|
|
|
% increase in mobile users in Brazil over the past three years
|
|
|
Number of TiVo and Tim and Claro subscribers
|
|
|
% of music company revenues that go into artist development
|
|
|
Number of hip hop and rock acts / bands / artists on MySpace
|
|
|
Number of genres music fans are open to listening to in the UK
|
|
|
Top selling album on iTunes in 2008
|
|
|
Number of unauthorized music files in 2008
|
|
|
% of music tracks that are downloaded without payment to the artist or the music company that produced them
|
|
|
Amount of loss attributed to file sharing in UK
|
|
|
Number of potential employment losses from piracy to music, film, and TV sectors in the UK
|
|
|
% of Internet users in Europe that regularly swap music on P2P networks
|
|
|
% of network traffic attributed to file sharing in Europe
|
|
|
% decrease in the number of album releases by new artists in France in first half of 2008
|
|
|
French share of new released albums domestically
|
|
|
Number of songs illegally downloaded in Spain in 2008
|
|
|
% of recorded music sales in Spain attributed to digital music
|
|
|
Number of films distributed on P2P networks in France in May 2008 compared to movie tickets sold
|
|
|
Number of 15-24 year olds in Europe that uses copyright infringing P2P networks
|
|
|
% of file sharing users that attributed their activity to the cost of music
|
|
|
% of people who downloaded music illegally in France who thought artists and authors should be paid for their work
|
|
|
Number of music consumers who downloaded music illegal because it's available for free
|
|
|
% of all Internet traffic attributed to P2P file sharing
|
|
|
% of UK music consumers would stop illegally downloading if told to do so by their ISP
|
|
|
% of French consumers who agree that internet account disconnection is a better approach than fines and criminal sanctions
|
|
|
% of American teenagers who are familiar with the law and think sanctions for illegal downloading are appropriate
|
|
|
% / percent of consumers who would stop illegally file-sharing after two warnings from their ISP
|
|
|
% / percent of Canadians who think parents should teach their children how to use the internet in a responsible way
|
|
|
Number of people who download unauthorized files online in the UK
|
|
|
% of UK movie downloaders who think the practice of downloading movies is too much work
|
|
|
% / percent of all online views in the U.S. of the 2008 Olympics took place on NBC’s platform.
|
|
|
Number of infringing web links removed by the IFPI to stop potentially hundreds of millions of unlicensed downloads.
|
|
|
% of students who download music and movies illegally
|
|
|
Number of illegal music downloads attributed to students in 2006.
|
|
|
US Recording industry revenue (physical music) - (2003 - 2012)
|
|
|
US Recording industry revenue (digital music) - (2003 - 2012)
|
|
|
Increase in the number of U.S. consumers 18-plus who watched online videos in 2008
|
|
|
Online video advertising revenues in 2009 and 2013
|
|
|
% of online video ad revenue that will be attributed to long-form video in 2013
|
|
|
CPM price of inventory on ad networks
|
|
|
% decrease in CPMs for ad-network-sold advertising
|
|
|
Average / Avg. Click-through rates (CTR) for advertising campaigns
|
|
|
CPMs for professional long-form videos in 2008 and 2013
|
|
|
CPMs for professional short-form videos in 2008 and 2013
|
|
|
Average CPM for User generated video ads in 2008 and 2013
|
|
|
% of streams attributed to user-generated videos
|
|
|
% of online video advertising revenue attributed to user-generated videos
|
|
|
2008 Stream Count Breakdown
|
|
|
2008 Ad Revenue Breakdown
|
|
|
% of Americans using the Internet more than one hour per day
|
|
|
Most trusted source for information about a company and, therefore, products.
|
|
|
Leading influencer of product purchases
|
|
|
Number one reason for choosing a particular website.
|
|
|
Influence of user reviews vs. professional reviews
|
|
|
One type of promotion that Adult Internet users considered most worthwhile.
|
|
|
Consumers trust friends above experts when it comes to product recommendations
|
|
|
Number one (1) influencer of consumer apparel and electronics purchases
|
|
|
Most credible form of advertising
|
|
|
The two leading reasons people contribute content to social shopping sites
|
|
|
Propensity of online social network users to trust their peers' opinions
|
|
|
% of consumers who said they would trust a friend's recommendation over a review by a critic
|
|
|
% of consumers that said they would trust user reviews over a critic.
|
|
|
% of UK social networkers that are more likely to buy a product as a result of a recommendation vs. non-social networkers.
|
|
|
Importance of user reviews relative to personal advice from a friend as the driver of purchase decisions
|
|
|
% of online holiday shoppers that read online customer reviews
|
|
|
% of consumers that read online business reviews before making purchasing decisions; % of whom say they trust these reviews.
|
|
|
% of consumers who read consumer-written product reviews on the Internet.
|
|
|
Sources of information consumers are "very likely" to consult before making a decision about their entertainment options
|
|
|
% of consumers who read reviews and share them with friends, family or colleagues, thus amplifying their impact.
|
|
|
As of October 2008, almost half of US online adults read ratings and reviews at least once a month, and Nearly twice as many read reviews compared with 2007. (The Growth Of Social Technology Adoption, Forrester, October 2008)
|
|
|
% of US online adults post ratings and reviews at least once a month.
|
|
|
% of shoppers intend to do their holiday gift buying online (versus in-store)
|
|
|
% of consumers who are planning to research products online prior to purchasing (vs. 65% in 2007).
|
|
|
% of consumers who strongly agree-that they choose companies and brands based on what others say online about their customer service experiences.
|
|
|
% of shoppers said they used product reviews to make decisions.
|
|
|
People who read a review were 30% more likely to purchase a product and visitors who wrote a review were 80% more likely to convert, based on analysis across several Coremetrics clients.
|
|
|
Among the 46% of respondents who had posted or planned to post reviews about their online shopping experience, the % that said those reviews either were, or would be positive.
|
|
|
% of those who read reviews that said that their purchasing decisions have been directly influenced by those reviews.
|
|
|
% of surveyed Internet users consulted other people's opinions online, making reviews the #1 resource for product research.
|
|
|
% of shoppers that deemed customer reviews as "extremely" or "very" helpful.
|
|
|
% of their users considered customer reviews to be more valuable than expert reviews.
|
|
|
% of consumers indicate they are more likely to purchase from a site if it has product ratings and reviews.
|
|
|
% consider the availability of customer reviews to be "very important" and "somewhat important".
|
|
|
% of respondents said they would trust a friend's recommendation over a review by a critic and % that said they would trust user reviews over a critic.
|
|
|
% of consumers earning more than $150,000 annually visit sites where customers review and rate products and services including restaurants.
|
|
|
% of UK online shoppers seek out ratings and reviews.
|
|
|
% of online consumers said they use the Internet to research everyday grocery products.
|
|
|
% of UK consumers research products via the Internet before shopping in a store.
|
|
|
% of millionaires say they always or often look at reviews before buying luxury goods; % of ultra-affluent shoppers use consumer reviews.
|
|
|
Size of Mobile user-generated content market worldwide in 2012 and 2007.
|
|
|
Satisfaction for those who recalled customer reviews on the retailers' site is 10% higher than those who said there were no reviews offered.
|
|
|
% of consumers that have a higher likelihood to purchase online when they read customer reviews
|
|
|
% of consumers that with a greater likelihood to purchase from the retailer next time they're buying similar merchandise
|
|
|
% of consumers that have a greater likelihood to recommend the site to others.
|
|
|
% of shoppers said online product evaluations and reviews influenced their purchasing decisions.
|
|
|
% of consumers who said they had done internet research on "everyday grocery products," and % that said they had done so for health and beauty products.
|
|
|
% of U.S. toy purchasers that are influenced by product reviews online.
|
|
|
% of online UK retailers that stated the main benefit of consumer-generated rating and reviews was that they improved site conversion rates.
|
|
|
% of online marketers that believe "media is in big trouble and will lose dollars to user-generated content."
|
|
|
% of retailers that have reviews
|
|
|
% of US retailers that said user-generated content would have a greater impact on their marketing goals in the near future.
|
|
|
Most important reasons merchants add customer reviews to their sites
|
|
|
By 2020, % of marketers that agree that building customer trust will become marketing's primary objective.
|
|
|
% of retailers that reported a increase in conversions as a result of adding reviews to their sites
|
|
|
% of marketers surveyed say that their social media spending will meet or exceed their traditional advertising spending within the next 5 years.
|
|
|
Positive effects of user-generated content as stated by UK website owners.
|
|
|
% of the 137 top retailers surveyed that offered customer ratings and reviews
|
|
|
% of online shoppers surveyed report that content is insufficient to complete research or purchase online "always, most often or some of the time."
|
|
|
% of consumers lost by online businesses due to lack of online product information
|
|
|
% of online shoppers would make purchases if sites offered increased interactive elements.
|
|
|
% of shoppers that said they left a store because of a lack of assistance.
|
|
|
% of UK shoppers that said they wish they could communicate directly with businesses - using live chat, forums or call-me-back facilities - via their websites; one in three require it from the UK businesses they currently use.
|
|
|
% of consumers said they prefer being able to find the answers they need online on their own if they had a question or wanted help while shopping online.
|
|
|
Traffic increase to question-and-answer Web sites from 2007 to 2008
|
|
|
Yahoo Answers user visits in February 2008
|
|
|
% of consumers trust "people like me" first for product advice.
|
|
|
% of online consumers that have left a site without purchasing multiple products because they couldn't get a question answered about one of the products in their shopping cart
|
|
|
% of online consumers that decided not to make a planned purchase because they couldn't readily find a piece of information about the product or service.
|
|
|
Conversion rates with and without product reviews
|
|
|
% of online UK retailers that reported that the main benefit of consumer-generated rating and reviews was that they improved site conversion rates.
|
|
|
Online travel buyer conversion rates after looking at TripAdvisor reviews on the Hayes & Jarvis site
|
|
|
Shoppers who browsed the site's new "Top Rated Products" page, which features products rated most highly by customers, had a 59% higher conversion rate than the site average and spent 16% more per order than other browsers of products.
|
|
|
Conversion rates and per order figures for shoppers who browsed "Top Rated Products" page on PETCO website
|
|
|
Sales impact of giving shoppers the ability to sort products within a category and by customer ratings
|
|
|
% more in price consumers are willing to pay for 4 and 5-star products
|
|
|
Top-rated products site navigation path featuring 4- and 5-star products in each category delivered 35% higher conversion and 40% higher average order value.
|
|
|
Increase in spending attributed to user reviews usage
|
|
|
% of Social Researchers (those who refer to user-generated content when shopping) research products online more than half the time, no matter where they ultimately buy the product (store, Web, catalog, etc.).
|
|
|
Online consumers are becoming precision shoppers. For every $1 in online sales, the Internet influenced $3.45 of store sales. (eMarketer, 2007)
|
|
|
% of those surveyed say they have a better overall shopping experience when they research products online before shopping in-store.
|
|
|
5% of adults that said they regularly or occasionally research products online before buying them in a store.
|
|
|
% of Internet users that reported using online reviews prior to paying for a service delivered offline.
|
|
|
Number of review users in nearly every category that reported that the review had a significant influence on their purchase, with hotels ranking the highest (87%).
|
|
|
% of those surveyed who said they made a purchase based on an online review said they found the review to have been accurate.
|
|
|
% increase in spending consumers who shop online for TVs and cameras vs. those that do not search online
|
|
|
Increase in email click through rates from reviews and ratings info in emails from PETCO
|
|
|
% increase in revenue per email for top rated product email vs. other email types
|
|
|
% of UK retailers who reported that consumer-generated activity leads to better search engine optimization.
|
|
|
% increase in purchase satisfaction and loyalty attributed to user reviews.
|
|
|
% increase in customer retention and loyalty at UK retailers as a result of user generated ratings and reviews.
|
|
|
% return rates decreased with use of reviews vs. those without reviews
|
|
|
Return rate of Products with 50+ reviews vs. those with less than 50 reviews.
|
|
|
% of the adults in the UK that say they use social networking because they like to participate with brands they favor.
|
|
|
% of people that don't believe that companies tell the truth in advertisements.
|
|
|
Impact on sales per session when sites allow customers to refine site search results by customer rating.
|
|
|
% increase in click through rates on RSS feeds with reviews that those without reviews
|
|
|
Number of Americans who will view online video at least once a month in 2007
|
|
|
% of online video viewers that watch news at least once a week
|
|
|
% of online video viewers that watch funny videos at least once a week
|
|
|
% of video viewers that have watched online video ads
|
|
|
% online video viewers that have taken an action based on ads they have seen
|
|
|
% of users that tell a friend about a video they have seen
|
|
|
Number of people in the us that went online to watch videos online in April
|
|
|
Average number of videos watched in April
|
|
|
% the total U.S. Internet audience that viewed an online video
|
|
|
The average number of minutes viewers watched videos online
|
|
|
Heaviest online video viewers (watched the most online videos)
|
|
|
Number of viewers and number of videos watched on YouTube
|
|
|
Number of videos watched per viewer on YouTube
|
|
|
Number of viewers and number of videos watched on YouTube
|
|
|
Number of videos watched per viewer on MySpace
|
|
|
The average online video duration
|
|
|
Number of online videos watched by US Internet users during November 2008.
|
|
|
Online video ad spending in 2013 and 2008.
|
|
|
Total Retail Sales - All Types, U.S.
|
|
|
Total E-Commerce Sales, U.S. (Excluding Travel)
|
|
|
Total Travel Sales Online
|
|
|
Internet Advertising Spending
|
|
|
Number of VOIP Subscribers, U.S.
|
|
|
Percent of U.S. Adults Online
|
|
|
Active Home Internet Users In the U.S.
|
|
|
Number of High Speed Internet Connections, U.S.
|
|
|
Number of Weblogs, Worldwide
|
|
|
Number of adult movies released by Hollywood per year
|
|
|
Number of homes that receive adult channels in scrambled form
|
|
|
Number of children with potential exposure to adult channels within homes
|
|
|
Number websites offering child pornography (which are illegal) worldwide.
|
|
|
Number of American adults in 2002 that admitted to seeing an x-rated movie in the last year.
|
|
|
Percentage of Porn movie rentals vs. non-porn movies in hotels in 2005
|
|
|
The average time a porn movie is watched in a hotel room
|
|
|
Time the average teenager spends per day watching television
|
|
|
% of the daily programming most frequently watched by adolescents that contains some sexual content
|
|
|
% of 13 year old boys in Alberta, Canada that admitted to viewing porn.
|
|
|
% of songs on ten top-selling CDs in 1999 that contained sexual content
|
|
|
Amount of revenues that, Comcast, the nation's largest cable company, pulled in from adult programming.
|
|
|
% of hotel guests that purchase adult entertainment when staying in big hotel chains such as Hilton, Marriot, Hyatt, Sheraton and Holiday Inn
|
|
|
How much does DirecTV make off of adult product?
|
|
|
% / percent of hotel chain profits can be attributed to in-room adult entertainment / pornography
|
|
|
Number of people the porn industry employs in California.
|
|
|
Amount of taxes the porn industry generates every year for the state of California.
|
|
|
Top reasons why people use porn.
|
|
|
% of all searches on file-to-file sharing systems that involved child or adult pornography.
|
|
|
% of movie searches that were for pornography
|
|
|
% percent of all P2P image searches that were for child pornography
|
|
|
% of all P2P searches that did not involve pornography or copyrighted materials
|
|
|
% of university students are having sex over webcams, instant messenger or the telephone
|
|
|
% of U.S. workers with an internet connection admitted to accessing an X rated website at work in the month of March 2004, as compared to 40% of home users and 59% of University users.
|
|
|
% of 1,500 surveyed companies that have terminated employees for inappropriate use of the Internet
|
|
|
% / percent of adults that believe it is ‘morally acceptable’ to look at pictures of nudity or explicit sexual behavior
|
|
|
% / percent of adults that believe it is ‘morally acceptable’ to have sexual thoughts or fantasies
|
|
|
38 percent of adults that believe there is nothing wrong with pornography use
|
|
|
% / percent of surveyed adults that indicated that their partner’s use of pornography made them feel insecure.
|
|
|
% / percent of surveyed adults that admitted they felt less attractive due to their partner’s pornography use.
|
|
|
% of Christians admitted to struggling with porn in their daily lives.
|
|
|
% of all Christian men and % of all Christian women who are addicted to pornography.
|
|
|
% of the women who answered the survey who admitted to having significant struggles with lust;
|
|
|
% of the church-going female participants that struggle with looking at pornography on an ongoing basis.
|
|
|
How students on the campus of a Christian campus deal with sexual purity
|
|
|
% / percent of the calls received on their Pastoral Care Line are for help with issues such as pornography and compulsive sexual behavior.
|
|
|
% of the men in attendance at a conference that were involved with pornography within one week of attending the event.
|
|
|
% of clergy admitted to having visited a sexually explicit Web site.
|
|
|
% of 81 pastors surveyed (74 males 7 female) that had been exposed to porn
|
|
|
% / percent of Christian leaders confirm that they are struggling with sexual addiction or sexual compulsion including, but not limited to use of pornography, compulsive masturbation, or other secret sexual activity.
|
|
|
% / percent of female readers of Today's Christian Woman's online newsletter admitted to intentionally accessing Internet porn in a recent poll.
|
|
|
% of the pastors had viewed Internet pornography within the last year
|
|
|
% percent of families said pornography is a problem in their home.
|
|
|
% of Christian men that admitted that they were feeling disconnected from God because lust, porn, or fantasy had gained a foothold in their lives.
|
|
|
Christian consumption of adult-oriented content
|
|
|
Revenues of the sex and porn industry in the U.S. and globally in 2006.
|
|
|
Worldwide sex industry sales for 2006.
|
|
|
% of all website visits that are sexual in nature
|
|
|
The No. 1 search term used at search engine sites.
|
|
|
% / percent of visitors to sex sites were spending so much time tracking down erotica on the computer that they were putting their real-life relationships and/or jobs at risk.
|
|
|
Demographics of visitors to adult content sites.
|
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% of those who visit websites with sexual content that say their Internet activities haven't affected their level of sexual activity with their partners
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Number of Online Video Users (2007 - 2012): 137.5 million (2007), 154.2 million (2008), 167.5 million (2009), 176.0 million (2010), 183.0 (2011), 190 million (2012)
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Number of owned dogs in the United States
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% / percent of U.S. households own at least one dog
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% / Percent of dog owners that own one dog
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% / percent of dog owners that own two dogs
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% / percent of dog owners that own three or more dogs
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Average number of dogs owned by dog owners
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The proportion of male to female dogs
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% / percent of owned dogs that were adopted from an animal shelter
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Average amount spent by dog owners on veterinary visits (vaccine, well visits) annually
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% / percent of owned dogs that are spayed or neutered
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Number of owned cats in the United States
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% / percent of U.S. households (or 38.4 million) that own at least one cat
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% / percent of cat owners that own more than one cat
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Average number of cats owned by cat owners
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Proportion of female cats owned vs. male cats
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% / percent of owned cats that were adopted from an animal shelter
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Amount spent by cat owners on routine veterinary visits
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% / percent of owned cats that are spayed or neutered
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% of U.S. households that own a pet
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In 1988, % of U.S. households that owned a pet as compared to 2006
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The amount of wood and paper we throw away each year
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% / percent of all fresh water on Earth that is in icecaps and glaciers.
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Number of pounds of CO2 into the atmosphere contributed with each gallon of gas used by a car
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Number of molecules of CFCs in a single Styrofoam cup
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Time it takes for a CFC atom to break up and become harmless once it reaches the ozone layer
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Number of Americans that live in areas with levels of air pollutants the federal government considers to be harmful.
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Amount of sewage Americans dump into their waters--every minute of every day.
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% of Earth's total water attributed to fresh water in lakes, streams, and rivers.
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Number of animals killed each year as the result of eating or being strangled in plastic.
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Number of Styrofoam coffee cups Americans throw away every year
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Number of plastic bottles thrown away by Americans every hour
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Number of glass bottles and jars thrown away by Americans
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Number of soft drink cans and bottles thrown away by Americans each year
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% / percent of a typical household's waste--including food scraps, yard waste, paper, cardboard, cans, and bottles--that can be recycled.
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Number of trees saved by using recycled paper for one print run of the Sunday edition of the New York Times.
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Number of trees saved per year if every American recycled just one-tenth of their newspapers
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Number of acres of tropical rainforests destroyed through logging or burning each year.
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% / percent of the 35,000 pesticides introduced since 1945 that have been tested for their effects on people.
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Raw materials needed to grow grains, fruits, and vegetables vs. those needed raise animals for meat.
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Gallons of water used every day by the typical American home
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Number of gallons of water wasted each month caused by a 1/32" leak in a faucet
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% / percent of the nation's total electricity consumption attributed to America's refrigerators
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Number of barrels of oil each day saved by Americans turning their heat down.
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Number of gallons of fresh water a single quart of motor oil can contaminate if disposed of improperly.
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Tons of carbon dioxide produced in a year caused by driving an average of 1,000 miles a month.
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Number of gallons of gasoline a year saved if all the cars on U.S. roads had properly inflated tires.
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The number of plastic bottles thrown into U.S. landfills each day.
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The number of barrels of oil saved each year by using public transportation.
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The number of servers found in American data centers, consuming more energy than over 300 million televisions found in American homes.
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The number of barrels of oil saved if 100,000 homes installed eco-friendly geothermal heating systems.
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The number of Chinese that die prematurely each year from respiratory illnesses and other diseases related to air pollution.
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The number of coal-fired power plants located in China. (One new power plant goes into operation every 4 to 7 days in China).
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The number of pounds a person would lose if they walked one half hour a day instead of riding or driving a motor vehicle.
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Amount of toxic releases reduced by Americans since 1970.
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Number of today's new automobiles to release the same number of emissions as of a 1960s model.
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Decrease in Carbon monoxide emissions (CO).
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Nitrogen oxide emissions produced by large utility and industrial boilers and other mechanical devices.
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Amount of sulfur dioxide emissions
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Decrease in volatile organic compounds
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Decrease in the amount of particulate matter emissions
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Decrease in lead emissions
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Decrease in lead emissions
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Recycling and composting rates
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Number of recycling programs in the United States (US)
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Number of composting programs in the United States (US)
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Container and packaging recycling increase
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% / percent of yard waste that was composted
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% / percent of all paper products that were recycled
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Decrease in the amount of MSW going to U.S. landfills from 1990 to 2005
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U.S. computer and video game software sales
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% / percent of American households that play computer or video games.
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The average game player age and how long they have been playing
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The average age of the most frequent game purchaser
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% / percent of all game players that are women.
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In 2008, % / percent of Americans over the age of 50 that played video games.
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% / percent of heads of households that play games on a wireless device, such as a cell phone or PDA, up from 20 percent in 2002.
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% / percent of all games sold in 2007 that were rated "E" for Everyone, "T" for Teen, or "E10+" for Everyone 10+.
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% / percent of game players under the age of 18 report that their parents are present when they purchase or rent games.
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% / percent of parents that believe games are a positive part of their children’s lives.
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Growth in the entertainment software industry from 2003 to 2006.
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GDP – In 2006, the entertainment software industry's value added to U.S. Gross Domestic Product (GDP).
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direct employment for the entertainment software industry for the four-year period 2002-2006
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Number of people directly and indirectly employed by Computer and video game companies.
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Number of American jobs projected to by provided by entertainment software companies by 2009.
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The average salary for direct employees in the entertainment software industry
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Top 5 States with the highest concentration of video game jobs.
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The largest employer of computer and video game personnel in the United States.
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Entertainment software industry impact on New Jersey economy.
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Computer and video game units sold and revenue in 2007.
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Game console software sales in 2007.
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Computer games sales and units sold in 2007.
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Portable software sales units sold in 2007.
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Average number of games sold every second of every day of 2007
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Best selling video game title of 2007
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Portable game units sold in 2007
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Fastest growing entertainment software category in 2007
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Average Age of Computer and Video Game Players
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Ages of Computer and Video Game Players
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% of American Households that play computer or video games
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Gender of Computer and Video Game Players
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Average Age of Computer and Video Game Buyers
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% of computer or video game players that are women, age 18 or older
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% of computer or video game players that are male, aged 17 or younger
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Average time gamers have been playing computer or video games
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% of gamers who play games with other gamers in person
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% of homes in America that have a video game console
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2007 Computer and Video Game Sales by Rating
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Top-Selling Video Game Genres in 2007 by Units Sold
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Top-Selling Computer Game Genres in 2007 by Units Sold
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Top-Selling Video Games of 2007
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Top-Selling Computer Games of 2007
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% of the time parents are present at the time games are purchased or rented
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% of parents believe games are a positive part of their children’s lives.
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% of the time children receive their parents permission before purchasing or renting a game.
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% of the time parents monitor the games their children play
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Top Four Reasons Parents Play Games
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% of parents that believe that the parental controls available in all new video game consoles are useful.
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% of parents that place time limits on video game playing.
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% of parents that place time limits on Internet usage.
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% of parents that place time limits on television viewing.
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% of parents that place time limits on movie viewing.
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Gender breakdown of those who play games online
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% of most frequent game players that say they pay to play online games
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Type of Online Game Played Most Often
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Number of Americans Who Play Games on Wireless Devices
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Video Game DOLLAR Sales (2006 and 2007)
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Computer Game DOLLAR Sales (2006 and 2007)
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Computer and Video Game Dollar Sales (2006 and 2007)
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Video Game UNIT Sales (2006 and 2007)
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Computer Game UNIT Sales (2006 and 2007)
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Computer and Video Game UNIT Sales (2006 and 2007)
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U.S. Computer and Video Game DOLLAR Sales (1996-2007)
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U.S. Computer and Video Game UNIT Sales (1996-2007)
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Number of Americans Who Plan to Buy Games in 2008
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Amount of complimentary product purchases stimulated by the entertainment software industry each year
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Amount in HD TV sales attributed to the Xbox 360 video game console
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Added value to GDP by the entertainment software industry
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Number of indirect and direct persons employed by the computer and video game industry
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Number of jobs projected by the computer and video game industry in 2009
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Average salary of a direct employee in the computer and video game industry
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Top 5 states with the highest concentration of computer and video game employees
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Number of employees in the top 5 states with the highest concentration of computer and video game employees
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Largest employer of video and computer game personnel in the US and number of people employed
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Amount of direct and indirect compensation to Californians in 2007
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Amount of portable software sales in 2007
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Number of video and computer games sold every second of every day in 2007
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Biggest opening sales weekend for a video game
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Number of portable game units sold in 2007
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Restaurants and hotel industry size
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Number of online gamers worldwide in 2007
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Restaurant Industry Sales in 2008
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Total Restaurant Locations
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Total Restaurant Employees
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Total Restaurant Industry Sales via Commercial Sector
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Total Restaurant Industry Sales via non-Commercial Sector
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Restaurant Industry Sales Forecasted Growth Rate for 2009
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The overall economic impact of the restaurant industry in 2009
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Additional jobs created for each million dollars generated in restaurant industry sales
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% of eating and drinking places having fewer than 50 employees
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Number people employed by the restaurant industry (% of US workforce)
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Number of jobs expected to be added by the restaurant industry over the next 10 years
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Demographics of eating and drinking place firm owners.
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% of all adults that have worked in the restaurant industry at some point in their lives
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Number of meal and snack occasions provided by the restaurant industry
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Number of daily American food service patrons
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% of adults that state their favorite restaurant foods provide flavor and taste sensations which cannot easily be duplicated in their home kitchen.
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Restaurant industry sales in a typical day in 2009
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Percent of adults who said they are trying to eat healthier now at restaurants than they did two years ago.
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Percent of adults who said they are more likely to visit a restaurant that offers locally produced food items. |