Case
Teaching Notes
Supplementary Resources
Abstract
Although Google had a stellar performance in Web search, many of its other services, such as Google Video, were less successful. This case describes how YouTube came to dominate the video market for user-generated content (UGC), while Google Video tried various entry strategies and ultimately failed, ending with the acquisition of YouTube. It also reviews the various competitors in the UGC market, chronicles the entry of established and new players in the area of professionally generated content (PGC), and outlines the key challenges related to monetizing the acquisition of YouTube for Google.
This case was prepared for inclusion in Sage Business Cases primarily as a basis for classroom discussion or self-study, and is not meant to illustrate either effective or ineffective management styles. Nothing herein shall be deemed to be an endorsement of any kind. This case is for scholarly, educational, or personal use only within your university, and cannot be forwarded outside the university or used for other commercial purposes.
2024 Sage Publications, Inc. All Rights Reserved
Resources
Exhibit 1: Unique Visitors for Online Video
Top Video Sites for August 2006 and 2007 (U.S., Home and Work)
Site | Aug. 2006 (in thousands) | Aug. 2007 (in thousands) | Percentage Change (%) |
YouTube | 34,039 | 56,453 | 66 |
vids.myspace.com | 17,923 | 16,759 | –6 |
Google Video | 13,483 | 14,450 | 7 |
AOL Video | NA | 13,632 | NA |
MSN Video | 11,984 | 12,486 | 4 |
Yahoo! Video | 5,958 | 11,987 | 101 |
Metacafe | 2,822 | 4,151 | 47 |
Break.com | 2,926 | 3,954 | 35 |
Veoh | 663 | 2,958 | 346 |
Atom Films | 1,102 | 1,422 | 29 |
Source: Nielsen/NetRatings, as cited on http://mashable.com/2007/09/13/nielsen-august.
Exhibit 2: Time Person of the Year
Source: Lev Grossman, “Time’s Person of the Year: You,” Time Magazine, December 13, 2006, http://www.time.com/time/magazine/article/0,9171,1569514,00.html.
Exhibit 3: U.S. Online Video Viewers, 2003–2010 (in millions)
Note: Ages 3+; online video viewer defined as an individual who downloads or streams video (content or advertising) at least once a month.
Source: David Hallerman, “Video Advertising Online: Spending and Audience,” eMarketer, July 2007.
Exhibit 4: User-Generated Online Video Content as a Percentage of Total Online Video Content Watched in the United States, 2006 and 2010(f)
Source: “User-Generated Online Video: Competitive Review and Market Outlook,” Screen Digest, January 2007.
Exhibit 5: Demographic Profile of U.S. Online Video Viewers, January 2006 (%)
Percentage of Respondents | |
GENDER | |
Male | 62 |
Female | 38 |
AGE | |
12–17 | 15 |
18–24 | 17 |
25–34 | 24 |
35–44 | 21 |
45–54 | 15 |
55–64 | 6 |
65+ | 2 |
EMPLOYMENT | |
Employed part/full time | 69 |
Retired | 3 |
Student | 20 |
Homemaker | 3 |
Unemployed | 4 |
Household income of $75,000+ | 45 |
RACE/ETHNICITY | |
White | 72 |
African/American | 11 |
Hispanic/Latin | 10 |
TYPE OF ACCESS TECHNOLOGY | |
Broadband | 81 |
Dial-up | 19 |
Plan to switch to broadband in next 12 months | 47 |
Source: Arbitron/Edison Media Research, “Internet and Multimedia 2006: On-Demand Media Explodes,” May 2006.
Exhibit 6: Demographic Profile of U.S. Online Video Viewers, February 2006 (%)
Heavy Viewers | Moderate Viewers | Light Viewers | Non-Viewers But Will This Year | Non-Viewers and Won’t This Year | |
GENDER | |||||
Male | 65 | 54 | 44 | 41 | 40 |
Female | 35 | 46 | 56 | 59 | 60 |
Age (mean) | 33 years | 37 years | 37 years | 38 years | 39 years |
MARITAL STATUS | |||||
Married | 40 | 54 | 46 | 61 | 50 |
Single | 41 | 23 | 25 | 14 | 18 |
Committed | 11 | 11 | 13 | 11 | 10 |
Divorced | 6 | 9 | 13 | 11 | 17 |
Household income $100,000+ | 11 | 7 | 7 | 4 | 7 |
SOCIOECONOMIC STATUS a | |||||
High | 17 | 17 | 20 | 8 | 11 |
Middle | 50 | 52 | 44 | 45 | 49 |
Low | 33 | 32 | 36 | 47 | 39 |
HIGH-SPEED INTERNET ACCESS LOCATION | |||||
Home | 85 | 79 | 72 | 59 | 61 |
Work | 86 | 83 | 81 | 73 | 71 |
a Combined measure based on income, education, and occupation.
Note: Heavy = weekly or more; Moderate = monthly but less than weekly; Light = less than monthly
Source: Online Publishers Association (OPA), “From Early Adoption to Common Practice: A Primer on Online Video Viewing,” February 2006.
Exhibit 7: How Video Viewers Engage in Use of Online Video (%)
Total | Men | Women | Age 18–29 | Age 30–49 | Age 50–64 | |
Receive video links | 75 | 75 | 75 | 76 | 77 | 71 |
Send video links to others | 57 | 59 | 54 | 67 | 55 | 45 |
Watch video with others | 57 | 58 | 57 | 73 | 58 | 34 |
Rate video | 13 | 15 | 10 | 23 | 11 | 4 |
Post comments about video | 13 | 15 | 10 | 25 | 9 | 5 |
Upload video | 13 | 16 | 9 | 20 | 12 | 5 |
Post video links online | 10 | 12 | 9 | 22 | 7 | 2 |
Pay for video | 7 | 8 | 6 | 10 | 7 | 3 |
Note: Margin of error is ±4% for all online video viewers (n=800). Margins of error for subgroups range from ±5% for male video viewers to ±8% for viewers ages 50–64. Video viewers ages 65 and older are not included in this table due to their small numbers (n=84).
Source: Pew Internet and American Life Project Tracking Survey, February 15–March 7, 2007. Taken from Mary Madden, Pew Internet and American Life Project, “Reports: Online Video,” July 25, 2007, http://www.pewinternet.org/PPF/r/219/report_display.asp.
Exhibit 8: Types of Videos Watched Online (% of adult Internet users)
Note: Margin of error is ±3% for all adult Internet users (n=1,492).
Source: Pew Internet and American Life Project Tracking Survey, February 15–March 7, 2007. Taken from Mary Madden, Pew Internet and American Life Project, “Reports: Online Video,” July 25, 2007, http://www.pewinternet.org/PPF/r/219/report_display.asp.
Exhibit 9: Online Video Viewing by Age and Type
Note: Margin of error is ±3% for all adult Internet users (n=1,492). Margins of error for subgroups range from ±4% for video viewers ages 30–49 (n=615) to ±8% for viewers ages 65 and older (n=202).
Source: Pew Internet and American Life Project Tracking Survey, February 15–March 7, 2007. Taken from Mary Madden, Pew Internet and American Life Project, “Reports: Online Video,” July 25, 2007, http://www.pewinternet.org/PPF/r/219/report_display.asp.
Exhibit 10: Dislikes about Online Video
Note: n=1,000 ages 18+.
Source: Synovate commissioned by ClipBlast!, February 2007.
Exhibit 11: Motivations for Uploading Videos
Source: McKinsey survey of 573 users of four leading online video-sharing sites in Germany, October 2006.
Exhibit 12: U.S. Internet Users Who Create User-Generated Content, February–March 2007
Note: User-generated content signifies creating own entertainment through editing own photos, movies, and/or music.
Source: Deloitte & Touche USA LLP, “State of the Media Democracy,” conducted by Harrison Group, provided to eMarketer, April 16, 2007.
Exhibit 13A: Online Video Advertising Spending, 2001–2011 (in millions)
Source: Paul Verna, “User-Generated Content: Will Web 2.0 Pay Its Way?” eMarketer, June 2007.
Exhibit 13B: Worldwide User-Generated Content Advertising Revenues, 2006–2011 (in millions)
Note: Includes ad revenues at user-generated video sites (e.g., YouTube), photo-sharing sites (e.g., Photobucket), and social networking sites (e.g., MySpace, Facebook).
Source: Paul Verna, “User-Generated Content: Will Web 2.0 Pay Its Way?” eMarketer, June 2007.
Exhibit 13C: U.S. User-Generated Video Streams and Associated Advertising Revenues, 2006, 2007, and 2011
Streams ($ in billions) | Ad Revenues ($ in millions) | |
2006 | 12.4 | 216 |
2007 | 28.5 | 515 |
2011 | 49.0 | 956 |
Note: Includes all video viewership and associated advertising revenues from online videos served by user-generated online video sites.
Source: Paul Verna, “User-Generated Content: Will Web 2.0 Pay Its Way?” eMarketer, June 2007.
Exhibit 13D: U.S. Online Video Advertising Spending Growth and Share, 2006–2010 (% increase vs. prior year and % of total online ad spending)
Percentage Change (%) | Share of Internet Total (%) | |
2006 | 82.2 | 2.6 |
2007 | 89.0 | 4.2 |
2008 | 67.7 | 6.0 |
2009 | 53.8 | 8.5 |
2010 | 45.0 | 11.5 |
Source: David Hallerman, “Internet Video: Advertising Experiments and Exploding Content,” eMarketer, November 2006.
Exhibit 14: Types of Online Video Advertising
Exhibit 15A: Estimated Current YouTube Revenue
Total video streams | 100,000,000 | Total video streams per day | ||
Streams on YouTube | 66,666,666 | At least 2/3 of videos seen on YouTube, rest embedded on other sites | ||
Page impressions | 66,666,666 | 1 video per page, 1:1 ratio | ||
Ad impressions | 66,666,666 | 1 ad per page, 1:1 ratio | ||
Pages sold at $5 CPM | 3,333,333 | 5% | Revenue @ $5 CPM = | $16,667 |
Pages sold at $2 CPM | 6,666,667 | 10% | Revenue @ $2 CPM = | $13,333 |
Pages sold at $1 CPM | 23,333,333 | 35% | Revenue @ $1 CPM = | $23,333 |
Pages sold at $0.75 CPM | 23,333,333 | 35% | Revenue @ $0.75 CPM = | $17,500 |
Pages sold at $0.50 CPM | 6,666,667 | 10% | Revenue @ $0.50 CPM = | $3,333 |
Pages sold at $0.25 CPM | 3,333,333 | 5% | Revenue @ $0.25 CPM = | $833 |
Subtotal revenue from display ads | $75,000 | |||
Subtotal revenue from homepage sponsorship ads | $175,000 | |||
Total daily revenue for YouTube from advertising | $250,000 | |||
Total monthly revenue for YouTube from advertising | $7,500,000 |
Source: Ashkan Karbasfrooshan, “YouTube IS Wildly Profitable—No Doubts about It,” Hipmojo.com, September 2007.
Exhibit 15B: Estimated Short- and Long-Term YouTube Revenue
Now | Conservative | Expected | Aggressive | ||
Monthly video streams a | 2,000,000 | 2,000,000 | 2,000,000 | 2,000,000 | 2,000,000 |
Percentage with ads b | 10% | 20% | 30% | 40% | 50% |
Videos with ads | 200,000 | 400,000 | 600,000 | 800,000 | 1,000,000 |
Percentage of ads watched c | 33% | 40% | 50% | 66% | 75% |
Total ads watched (in thousands) | 66,000 | 160,000 | 300,000 | 528,000 | 750,000 |
CPM | 10 | 20 | 30 | 40 | 50 |
Monthly revenue | $660,000 | $3,200,000 | $9,000,000 | $21,120,000 | $37,500,000 |
Annual revenue | $7,920,000 | $38,400,000 | $108,000,000 | $253,440,000 | $450,000,000 |
a Based on Comscore 1.7 billion in May.
b Ads currently only on partner videos.
c 75% in recent tests.
Five Years From Now | Conservative | Expected | Aggressive | ||
Monthly video streams a | 10,000,000 | 20,000,000 | 30,000,000 | 40,000,000 | 50,000,000 |
Percentage with ads b | 50% | 55% | 60% | 65% | 70% |
Videos with ads | 5,000,000 | 11,000,000 | 18,000,000 | 26,000,000 | 35,000,000 |
Percentage of ads watched c | 33% | 40% | 50% | 55% | 60% |
Total ads watched (in thousands) | 1,650,000 | 4,400,000 | 9,000,000 | 14,300,000 | 21,000,000 |
CPM | 10 | 20 | 30 | 40 | 50 |
Monthly revenue | $16,500,000 | $88,000,000 | $270,000,000 | $572,000,000 | $1,050,000,000 |
Annual revenue | $198,000,000 | $1,056,000,000 | $3,240,000,000 | $6,864,000,000 | $12,600,000,000 |
a Based on Comscore 1.7 billion in May.
b Ads currently only on partner videos.
c 75% in recent tests.
Source: Henry Blodget, “Analyzing YouTube’s Revenue Potential,” Silicon Valley Insider, August 2007.
This case was prepared for inclusion in Sage Business Cases primarily as a basis for classroom discussion or self-study, and is not meant to illustrate either effective or ineffective management styles. Nothing herein shall be deemed to be an endorsement of any kind. This case is for scholarly, educational, or personal use only within your university, and cannot be forwarded outside the university or used for other commercial purposes.
2024 Sage Publications, Inc. All Rights Reserved