Project “Tipping Point”
OPIM 469: Information Strategy and Economics
Ursina Beerli, Steven Gao, Juhi Heda, Grant Wilson
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The blog entry featuring this analysis can be found on the ChubbyBlog @ http://www.chubbybrain.com/blog
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Agenda
Introduction & Motivation “Tipping Points” Student Survey Analysis Interface Insights Case Study: Yelp! versus Citysearch Fun Stuff Appendix
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Questions
• For a two‐sided network (and user generated) website, what factors lead to a “tipping point” after which growth becomes exponential? • What are the implications of the way college students use these types of websites today? • For websites that share a similar purpose, what determines the success of one over the other(s)?
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Motivation
A lot of literature about two‐sided networks exists but there is not much about internet based ones and user generated content websites, especially in regards to this “tipping point”.
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The economics behind two-sided networks
Definition: markets where the value of an agent in one market is related to the number of actions taken by agents in another market
Price Product 1 Price Product 2
Externality (2 1)
Externality (1 2 )
Quantity
Quantity
Network Effects: Markets in which the value for one agent is affected by the number of actions of other agents Externalities: action of one agent affects the value of another
Source: Economics of Two-sided Market by Prof. Lorin Hitt Published with permission on www.chubbybrain.com
Who’s in your network?
Profile users Video viewers Commenters Readers Application developers Advertisers Video creators Advertisers Reviewers Advertisers
Wikipedia users
Wikipedia contributors
Readers
Reviewers Advertisers
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Website profiles
URL Founded Traffic Rank Type
Facebook.com Feb. 2004 5 Social networking Limited
YouTube.com Feb. 2004 3 Video sharing
Wikipedia.org Jan. 2001 8 Online collaborative encyclopedia None
Yelp.com Oct. 2004 613 Social networking, user review, and search Ad sponsors
Citysearch.com Sept. 1995 845 Online city guide
Ads
Integrated
Pay for performance
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Top sites linking in: having several high traffic websites linking in may drive own traffic
•Youtube.com •Wikipedia.org •Google.com •Hi5.com •Fotolog.com
•Hi5.com •Google.com •Fotolog.com •Google.fr
•Google.com •Fotolog.com •Metroflog.com •Wretch.cc •Flickr.com •Google.es
•Google.com •Google.de •Google.jp •Digg.com •Flickr.com •Livejournal.com
•Google.com •Google.co •Match.com •Cnn.com •Ask.com
Source: Alexa.com Published with permission on www.chubbybrain.com
Agenda
Introduction & Motivation “Tipping Points” Student Survey Analysis Interface Insights Case Study: Yelp! versus Citysearch Fun Stuff Appendix
Published with permission on www.chubbybrain.com
Active Users (millions)
Question: How can we assess the growth of these websites?
Number of Active Users over Time
60 50 40 30 20 10 0 8/1/2004 2/17/2005 9/5/2005 3/24/2006 10/10/2006 4/28/2007 11/14/2007
Time
Active users data and Google Insights index data for Facebook yield similar graphs over time. This implies that Google Insights data can be used as a reasonable proxy for active user data that was more difficult to find for other websites.
Google Insights Index over Time
100 90 80 70 60 50 40 30 20 10 0 1/4/2004 1/4/2005 1/4/2006 1/4/2007 1/4/2008
Index Value
Time
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100 90 80 70
Time Between Launch and Tipping Point: 3.4 years: (06/07 – 02/04)
Index
60 50 40 30 20 10 0 01/04/04 07/04/04 01/04/05 07/04/05 01/04/06 07/04/06 01/04/07 07/04/07 01/04/08 07/04/08
Chronological Timeline:
September 2005: Facebook expands to include high school networks September 2006: Facebook expands registration so that anyone can join June 2007: Facebook unveils platform for developers of social applications (launches with 65 developer partners and over 85 applications) October 2007: Facebook launches platform for mobile October 2007: Microsoft invests in Facebook
06/03/2007
Date
0.4
Change in Index Value/ Week
0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 10/6/2003 10/5/2004 10/5/2005 10/5/2006 10/5/2007 10/4/2008
November 2007: Facebook unveils Facebook ads April 2008: Facebook launches Facebook chat
Date
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100 90 80 70
Time Between Launch and Tipping Point: 4.1 years: (02/05 – 01/01)
Chronological Timeline:
February 2004: Yahoo! includes Wikipedia in Content Acquisition program which leads to more indexing. Also, new servers are installed after a computer crash took wiki offline for a week in December.
08/04/04 03/04/05 10/04/05 05/04/06 12/04/06 07/04/07 02/04/08 09/04/08
Index
60 50 40 30 20 10 0 01/04/04
May 2004: Wikipedia introduces categorization. September 2004: Millionth article posted on Wikipedia. January 2005: Wikipedia.org domain changed from a redirect to English Wikipedia to a portal showing all Wikipedia languages that have over 100 articles.
Date
0.12 0.1 0.08 0.06 0.04 0.02 0 10/6/2003 10/5/2004 10/5/2005 10/5/2006 10/5/2007 10/4/2008
02/20/2005
Change in Index Value/ Week
Jan 2007: Esperanza (Spanish rival) is disbanded and former users turn to Wikipedia. July 2008: Google launches Wikipedia rival Knol.
Date
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100 90 80 70 60
Time Between Launch and Tipping Point: 2.1 years: (11/06 – 10/04)
Chronological Timeline:
November 2005: Yelp receives $3M VC funding. July 2006: Yelp! wins CNET award as top student site. October 2006: Yelp! Gets $10M funding to help it expand to other metropolitan cities outside of San Francisco. Also enters the fashion scene with launch of Lifestyle Apparel Line. February 2008: Yelp! Gets additional $15M in funding and opens a New York Office to speed up the adoption on the East Coast. July 2008: Yelp! Announces the launch of “Yelp! For Business Owners”. July 2008: Yelp! launches native application for iPhone.
Index
50 40 30 20 10 0 07/04/04 01/04/05 07/04/05 01/04/06 07/04/06 01/04/07 07/04/07 01/04/08 07/04/08
Date Change in Index Value/ Week
0.25 0.2 0.15 0.1
11/05/2006
0.05 0 7/8/2003 7/7/2004 7/7/2005 7/7/2006 7/7/2007 7/6/2008 7/6/2009
Date
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Time Between Launch and Tipping Point: 2.1 years: (03/06 – 02/04)
100 90 80 70 60
Chronological Timeline:
February 2006: SNL releases wildly popular video clip “Lazy Sunday” in Dec. 05 which leads to great popularity until NBC Universal asks YouTube to take it down. Generates a lot of publicity. March 2006: First ads appear on YouTube. September 2006: Warner Music signs deal allowing YouTube to host WM videos for portion of ad income. October 2006: YouTube bought by Google for 1.65 billion in stock. January 2007: Founder announces that online video service will pay active user‐contributors a portion of website ad revenue. March 2008: YouTube announces “YouTube Everywhere” which allows third party develops to access YouTube’s videos. November 2008: YouTube partners with MGM, CBS, and Lions Gate to post full length films and T.V shows to compete with Hulu.
Index
50 40 30 20 10 0 01/04/05 07/04/05 01/04/06 07/04/06 01/04/07 07/04/07 01/04/08 07/04/08 01/04/
Date
0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 10/6/2003 10/5/2004
Change in Index Value/ Week
03/26/2006
10/5/2005
10/5/2006
10/5/2007
10/4/2008
10/4/2009
Date
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100 90 80 70 60
Chronological Timeline:
Mid 2006: Yelp! begins expanding to metropolitan cities outside of San Francisco and “takes off”. October 2006: Citysearch launches mobile services. December 2006: Citysearch content becomes available through ask.com’s AskCity. March 2007: Citysearch acquires InsiderPages . With over 600,000 customer reviews and over 2.5 million people, InsiderPages.com was created to help people find the best local businesses through recommendations from their friends and neighbors. August 2007: Citysearch adds menus to restaurant profiles.
10/5/2004 10/5/2005 10/5/2006 10/5/2007 10/4/2008
Index
50 40 30 20 10 0 07/04/04 01/04/05 07/04/05 01/04/06 07/04/06 01/04/07 07/04/07 01/04/08 07/04/08
Date
0.1
Change in Index Value/ Week
0.05 0 10/6/2003 ‐0.05 ‐0.1 ‐0.15
04/23/2006
January 2008: “Eat It” application allows Facebook users to share reviews with friends. February 2008: AOL and Citysearch announce strategic content and advertising partnership.
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Date
Takeaways
• Providing incentives or access to third party developers can increase network effects and expand user base. (Facebook) • Increasing global appeal can increase user base. (Wikipedia) • Targeting users in popular metropolitan areas may be a strategic way to propel traffic and website use. (Yelp!) • Sometimes macro events beyond your control can greatly affect traffic. It’s up to you to take advantage of this by finding ways to appeal to a network that might benefit from your traffic. (YouTube) • Unfortunately, due to no “fault” of your own, another website with a similar mission may negatively affect your own user base. Be prepared, and find ways to add value for consumers in a way that your competition can’t, either through content or through other features such as ease of use, sophistication of interface, etc. (Citysearch)
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Agenda
Introduction & Motivation “Tipping Points” Student Survey Analysis Interface Insights Case Study: Yelp! versus Citysearch Fun Stuff Appendix
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Demographic information of survey respondents
Survey Respondents Demographics
100% 90% 80% 70% 60% 50% 40% 30% 20% 10% Freshman 0% n University Year Major Penn Arts & Sciences 160 Junior Other Senior Engineering Nursing Business Other Alumni Multiple
Sophomore
Source: Student Survey, n=260 Published with permission on www.chubbybrain.com
Quality of content is by far the most important characteristic
Importance of Website Characteristics
Importance (1‐least important, 10‐most important) 5.2 5.1 5 4.9 4.8 4.7 4.6 4.5 4.4 4.3 4.2 4.1
Source: Student Survey, n=260; Quality of content, n=209; Amount/quality of content by others, n=210; Searchability, n=212; Amount of content, n=212; Update speed, n=212; Level of privacy available, n=211; Sophistication of interface, n=211; Number of friends, n=212; Level of moderation, n=208; Network, n=210 Published with permission on www.chubbybrain.com
Usage and contribution is high for Facebook, YouTube, and Wikipedia
How often do you use each of the following websites?
250 # of respondents # of respondents 200 150 100 50 0 Never 1‐5 times per month 6‐10 times per month 10+ times per month Daily or almost daily 250 200 150 100 50 0 Never 1‐5 times (per month) 6‐10 times (per month) 10+ times (per month) Daily or almost daily
How often do you contribute to each of them?
Source: Student Survey, n=260 Published with permission on www.chubbybrain.com
Boredom and ease are the most popular motivations for contributing
What is your motivation for contributing to these websites?
180 160 140 # of respondents 120 100 80 60 40 20 0 Fun to do when you’re bored It’s easy to do Easy platform Can reach a wide Want to for expressing audience establish and/or creativity share expertise on a topic Other
Source: Student Survey, n=260 Published with permission on www.chubbybrain.com
Non-contributors would contribute more if given monetary incentives
Monetary Incentive
250 200 150 100 50 0 Respondents 250 200 150 100 50 0 Respondents
Status Incentive
Don’t know No Yes
Don’t know No Yes
Source: Student Survey, n=260 Published with permission on www.chubbybrain.com
Successful websites replace others
•MySpace •Xanga •Hi5 •Orkut •Friendster •LinkedIn •University directory •AIM •Wayn •Lokalisten
•Google Video •AOL Video •Break.com •Yahoo Music Videos •MTV Music Videos •iTunes •Limewire •Revver
•Google & other search engines •Ask •Books & encyclopedias •Britannica •Encarta •Dictionary.com •Ask Jeeves
•Citysearch •Yellow pages
•Guidebooks
Source: Student Survey, n=260 Published with permission on www.chubbybrain.com
Takeaways
• Quality of content is perceived as most important, despite the fact these websites are user‐generated. • Most people don’t perceive the network to be important, even though network effects greatly influence the success of these websites. • Some user‐generated websites rely on a small group of dedicated fans to contribute, though several more people use them. • A monetary incentive may be one way to grow the user base until it reaches a “tipping point”.
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Agenda
Introduction & Motivation “Tipping Points” Student Survey Analysis Interface Insights Case Study: Yelp! versus Citysearch Fun Stuff Appendix
Published with permission on www.chubbybrain.com
Facebook over three years
August 06, 2005 August 13, 2005 January 15, 2006
January 5, 2007
August 3, 2007
December 3, 2008
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Wikipedia over eight years
July 27, 2001 September 25, 2001 September 30, 2002
August 4, 2003
April 27, 2006
December 3, 2008
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YouTube over eight years
April 28, 2005 June 22, 2005 November 24, 2005
January 16, 2006
November 18, 2007
December 3, 2008
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Yelp! over four years
October 3, 2004 October 17, 2004 August 3, 2005
October 29, 2005
August 15, 2006
December 3, 2008
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Citysearch over eight years
May 11, 2000 October 19, 2000 October 11, 2001
March 21, 2003
September 15, 2007
December 3, 2008
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Takeaways
• Create an identity! Maintaining a color scheme, logo, or layout may help users recognize and associate with a website. Without a cohesive image, consumers may use your website without even thinking about the “brand”. (Citysearch) • Cut the clutter if possible. (Facebook, Wikipedia) • The use of a “teaser” home page pre‐launch may be a strategic way to create hype. (Yelp!) • Constantly displaying fresh data on the homepage may persuade users to come back often. (Yelp!, YouTube)
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Agenda
Introduction & Motivation “Tipping Points” Student Survey Analysis Interface Insights Case Study: Yelp! versus Citysearch Fun Stuff Appendix
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Yelp! Vs. Citysearch
Number of unique visitors to Citysearch has been declining while number of unique visitors to Yelp! has been increasing.
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Yelp! Vs. Citysearch
Restaurant listings on mobile Restaurant profiles on mobile
Citysearch’s mobile application launched just a few months after Yelp!’s and looks very similar. Competition is getting fierce and each company must find a unique competitive advantage to secure and maintain users.
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Yelp! Vs. Citysearch
Yelp! City Search
• Grouped around large metropolitan areas (+) • 4 years old • Centered around San Francisco and slowly expanding to major metro areas (+) • Consistent brand image (+) • Cultish following centered by its focus in California
• Over 75,000 cities of all sizes • 13 years old • Database a result of years of acquisitions and widespread use • Rocky history centered around numerous acquisitions • Recently revamped data center reorganized about neighborhoods
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Agenda
Introduction & Motivation “Tipping Points” Student Survey Analysis Interface Insights Case Study: Yelp! versus Citysearch Fun Stuff Appendix
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It Pays to have Pals
• PayPal is a start‐up forming machine
– YouTube – LinkedIn – Yelp!
• Innovative process
– Bring together smart people – Get funding from connections in PayPal
• Former employees who started VC’s
• Start‐up success is very circular—those who succeed tend to succeed again. • It’s about the network!
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Impact of the Day of the Week
Both YouTube and Facebook see recurring weekly increases on Saturday, Sunday, and Monday (likely as an extension of Sunday night).
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Impact of the Day of the Week
The weekend: Gives YouTube a boost . Gives Facebook a slight bump. Causes Wikipedia a slight decrease in users.
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Seasonal Effect on Websites
The seasonal effect on YouTube is tenuous – could be extrapolation.
Without research papers due the next day in school, Wikipedia suffers.
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Takeaways
• Do weekly and seasonal effects have implications for advertisement cost structure or bandwidth use and allocation?
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Opportunities for Further Analysis
"The probability of adopting by those who have not yet adopted is a linear function of those who had previously adopted.“ –Professor Bass p: the “coefficient of innovation” q: “the coefficient of imitation” (reflects the influence of previous adopters) The Bass Model is the most widely applied new‐product diffusion model. It has been tested in many industries and with many new products (including services) and technologies.
1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
M * cF M * cF_asSumf M * DE_cF_asSum_DE_f
140,000 120,000 100,000 80,000 60,000 40,000 20,000 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 Published with permission on www.chubbybrain.com
Appendix
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Penn vs. Non-Penn ratings of characteristics
Importance of Website Characteristics
6.0 5.0 4.0 3.0 2.0 1.0 0.0 Penn Non-penn
Source: Student Survey, n=260 Published with permission on www.chubbybrain.com
Penn students use all websites more frequently
Penn vs. Non‐Penn Usage
100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 10+ times per month Daily or almost daily 6‐10 times per month Never 1‐5 times per month
Source: Student Survey, n=260 Published with permission on www.chubbybrain.com
Penn students contribute less frequently to YouTube and Wikipedia
Penn vs. Non-Penn Contribution
100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Daily or almost daily 1-5 times (per month) 6-10 times (per month) 10+ times (per month) Never
Source: Student Survey, n=260 Published with permission on www.chubbybrain.com
Wiki article graph
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Wikipedian protester
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