Data Business

1. The Networked Economy (9) : Information Management, Strategy, and Innovation网络经济：信息管理，战略和创新 Data Business

2. Google data sources • Search • Query sequence • Choice set • Which link the user chooses • Queries and their refinements, clicks on links and returns • Use individually and in the aggregate • Use: Search quality • Use: Trends • Gmail • Content and social relationships • Opening up the social graph (Orkut) • Response behavior: model • Use: relevance ranking • Use: Discovery • Spam • Mark as spam

3. Google data sources • Toolbar • Since 2002 • Follow user across sites • Always with user, give data to get data • Notes • Annotate web pages • Analytics • Javascript embedded by site owner • Gives insight e.g., on how popular a given link is • Insight in what people do going through websites • Reader • Read, Mark, Save, Tag • Forward to friend • Docs • Content and social relationships

4. Google data sources • Google groups • Vs Wiki / Google docs • Talk • E.g., chat on webpage • Maps • Intent • Repository of 3D objects • UGC, being able to change info (200m) • Location • Phone: My Location feature • GPS • Calendar • Future

5. Google data sources • Design tools for home • Creates qualified leads for e.g., window manufacturer • Checkout • From the cradle to the grave • For purchases of higher priced items, process of learning about product dimensions etc • Payment systems • Google checkout is a low margin business that drives the high-margin business of ads

6. The Consumer Data Revolution • The First Data Revolution • Example: Amazon.com • Mainly implicit data, some explicit data • The Second Data Revolution • Example: Facebook • Mainly explicit data • Customers start interacting • The Consumer Data Revolution • How the attitudes of individuals to their info is changing

7. Focus on Interactions • Who knows about your relationships with others? • How does Google (or Amazon) differ from IBM (or Microsoft)? • Past, present and future • Past • Given data, get me insights • Present • Given problem, get me data • Future: Consumer data revolution • I give you data, you give me money! • Framework • Architectures of experimentation (Web1) • Give set of possible actions, do experiments • Architectures of participation (Web2) • Architectures of interaction (Web3)

8. Communication, Computation and Information • 1970’s • “Experts” learn a language the computer understands • Digitizing back office • 10M people • 1980’s • Front office interacts with back office • 100M people • 1990’s • Customers interact with firm • Search: 1bn people poking at stuff • 2000’s • 1bn people poking at stuff • 100M people producing stuff • Peer-production and collaboration • Customers interact with customers • Now • Discovery in addition to search • Serendipity: Discover what not searched • People in addition to pages • Social commerce • Mobile in addition to PC (and paper) • Continuous partial attention • Model current situation plus history • Sensing

9. Survey 调查问卷 • “…. Please let us know what you plan to do at Amazon.com today”“……请告诉我今天你计划在亚马逊网站上做什么” • Free responses, hand-coded into non-exclusive categories自愿回复，将回复进行分类编码，归入一些非互斥的类型 • Multiple assignments possible可能回复多种可能 • Average: 1.2 categories per response平均：每个回复涵盖1.2个种类 • Number of responses: 1023回复数量：1023 • Response rate: 3.1%回复率：3.1% • Date: February 11-12, 2003日期：2003年二月11-12日

10. Why do people visit?　为何访问网站

11. Why do people visit?　人们为什么访问网站？

12. Stated vs revealed preferences 自认的偏好与实际的偏好 • Obtain insights by combining individual survey response with click analysis:结合个人调查问卷的回复与点击情况分析，得出一些结论 • Look at those who ended up buying something:最终购物的网民中 • Only about one-half of those making a purchase indicated that they wanted to buy something in this visit只有1/2事先称计划购物 • Look at those who said they wanted to buy something:最初想来购物的网民中 • Only about one-third of those indicating intent to buy ended up making a purchase in that visit只有1/3最终完成购物  

13. Let Amazon.com access your camera and microphone? • November 2007 • Adobe Flash installed on820 million Internet-connected computers and mobile devices

14. Integrated Media Measurement Inc • IMMI • Listening into your room • every 30 seconds, • for 10 seconds.

15. Data at the heart of the Digital Networked Economy • Clicks • Music • Dating

16. Give data to get data about applicants (JobScore) • Use information about candidates from interviews at other companies

17. 加入购物车

18. 加入购物车 戴维斯的专辑 Also want to make recommendations!添加推荐! 去收银台 等一下！再加16.01美元就能……

19. 购买戴维斯专辑的消费者 也买了另两张专辑 想买戴维斯专辑的消费者 同时浏览了其它同类专辑 Also want to make recommendations!添加推荐! • Substitutes (buy instead of)替代（选择购买） • Customers who shopped for X also shopped for Y (based on clicks)Z买了X的消费者也会再 • Complements (buy in addition to)互补（额外购买） • Customers who bought X also bought Y买了X的消费者会再买Y

22. Result: Right vs Left对比结果：左还是右 • Metrics　衡量标准 • Conversion rate: Percentage of visits placing an order转化率：下订单的浏览者所占的比例 • Order size: Number of additional (from the second page) items put into cart 订单大小：（从第二页起）新购商品数量 • Result　结果 • “Your Shopping Cart” on right is about 1% better than on left “Your Shopping Cart”置于右侧比置于左侧的效果提高1%

23. Communication

24. The Data Business: Who Pays Whom? • Value of data proportionally to their impact on decisions • Traditional data business • Acxiom • Who do I send my advertisements to? • (economics of communication) • Maps • What route do I take? • (discussed earlier) • OAG • What flight suits me best? • (user generated, screen-scraped) • MLS (Multiple listing service) • What house do I buy? • (user generated: Zillow, Redfin, Trulio) • Contacts • Who do I sell to? Hire? • (LinkedIn, jigsaw)

25. Buy and trade business cards (Jigsaw) • 7M business cards (2007.12) • 200k members • Community corrects • Loss of control

26. Where do people go for information? • 20 years ago: Produced news • Publicized opinion • 10 years ago: Search • Search: Already know what you are looking for • Discovery: Find something you didn’t know you were looking for (Serendipity) • Blogs, Wikipedia • Now: Social network • Discover via people you are connected to • “Generation C”

27. Viral Marketing • Only 14% of people believe information passed to them by government and advertising • 90% of people believe information passed to them by friends and family • 80% of all consumer decisions are influenced by word-of mouth • 89% of consumers recommend products or services that they like to others. • Word-of-mouth is 9X as effective as advertising in converting unfavorable or neutral pre-dispositions into positive attitudes • Word-of-mouth is 4X as effective as personal selling in influencing consumers to switch brands • Viral Marketing works well because context, content, and targeted individual (recipient) are chosen by a friend

28. The Consumer Data Revolution: Who Pays Whom? • What does Google know about you? • Key: Users now actively contributing data • Four stages • The data business • Summary • Data companies pay employees to create data • Implicitly generated data (traces) • Experiments • Users contribute data • Incentives • Data about themselves, about others, about relationships • (not binary) • Users expect value for themselves

29. Thank you! Andreas Weigend+1 (650) 906-5906andreas@weigend.comwww.weigend.comwww.weigend.com/blog