Networked Markets

Ashish GoelMukund Sundararajan

Networked Markets

• Markets that could not have been possible without the Internet “at scale”

• Will briefly describe the concepts and business ideas underlying these markets

• Will largely focus on the mathematical and technical aspects that lie at the heart of how these markets use and are used by human beings

• Can not cover all these technical topics in great detail, but will give you a good understanding of the underlying technical ideas

Examples

Business: Groupon

Technical ideas: Group Action; Network Formation; Virality

Examples

Business: Netflix and Amazon

Technical ideas: The long tail of human interests; personalization; reviews and ratings

Examples

Business: eBay

Technical ideas: The long tail of production; new pricing models; reputation systems

Examples

Business: TripAdvisor, Yelp

Technical ideas: Reviews and ratings

Examples

Business: Mechanical Turk and oDesk

Technical ideas: crowdsourcing

Examples

Business: Search

Technical ideas: Crowd-sourced reputation systems; advertising networks

Examples

Business: Social networks, social media

Technical ideas: advertising networks; personalization

Examples

Business: Online retail and advertising

Technical ideas: targeting; personalization; different pricing models for advertisements

Examples

Business: Ashley Madison

Technical ideas: privacy

Examples

Business: Silk Road

Technical ideas: virtual currencies; anonymity

Examples

Business: Peer-to-Peer Content Sharing

Technical ideas: reputation systems; virtual currencies; anonymity

Examples

Business: Online education

Technical ideas: peer grading (similar to reviews and ratings)

Technical Topics Covered– Groupon: Group action; network formation; virality– Netflix and Amazon: The long tail of human interests; personalization; reviews

and ratings– eBay: The long tail of production; new pricing models; reputation systems– TripAdvisor, Yelp: Reviews and ratings– Mechanical Turk and oDesk: distributed work– Search: Crowd-sourced reputation systems; advertising networks– Social networks, social media: advertising networks; personalization– Online retail and advertising: targeting; personalization; different pricing models

for advertisements– Ashley Madison: privacy– Silk Road: virtual currencies; anonymity– Peer-to-Peer Content Sharing: reputation systems; virtual currencies; Anonymity– Online education: peer grading (similar to reviews and ratings)

Today: Long Tails

• Long tails are the signature of human activity.– Christos Papadimitriou

• Popularized by an article in “Wired” by Chris Anderson– Details in a book called “The Long Tail” by Chris Anderson

• Another interpretation: Long tails are a balance between human individuality and social behavior

• Technical details in notes

Implications of Long Tails

• Challenges for search: search keywords are diverse; can not just process the top few keywords offline; need to assemble search results in real-time!

• Opportunities for advertising: search keywords express intent; advertisers can use the long tail of search to sell a long tail of products

Implications of Long Tails

• Example: Blinds.com . Started 1996, and soon grew to be a large business.

• Blinds are a product in the long tail: they are bought infrequently, but the total demand is still quite large when aggregated over a country (Blinds.com has > 50M in revenues)

• The Internet allowed them to have a virtual storefront

• Search advertising allowed them to reach the long tail of customers very efficiently

Implications of Long Tails

• Example: Netflix’s DVD business• DVD licensing fees per rental are negotiated

between Netflix and the studios; depend on popularity of the movie

• If Netflix rents out a less popular DVD, its costs are lower

• Enter the recommendation system: by offering you personalized recommendations, Netflix makes good use of the long tail in people’s tastes