Data Business
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© people & data | www.weigend.com Andreas S. Weigend, Ph.D. 韦韦韦韦韦 The Networked Economy (9) : Information Management, Strategy, and Innovation 网网网网 网网网网网 网网网网网 ：， Data Business
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The Networked Economy (9) : Information Management, Strategy, and Innovation 网络经济：信息管理，战略和创新. Data Business. 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 - PowerPoint PPT Presentation
Transcript of Data Business
© people & data | www.weigend.com Andreas S. Weigend, Ph.D. 韦思岸教授
The Networked Economy (9) : Information Management, Strategy, and Innovation网络经济：信息管理，战略和创新
Data Business
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0 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 aggregateUse: Search quality Use: Trends
Gmail Content and social relationships Opening up the social graph (Orkut) Response behavior: modelUse: relevance rankingUse: DiscoverySpam Mark as spam
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0 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
DocsContent and social relationships
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0 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
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0 Google data sources
Design tools for home Creates qualified leads for e.g., window manufacturer
CheckoutFrom the cradle to the graveFor purchases of higher priced items, process of learning about product dimensions etc Payment systemsGoogle checkout is a low margin business that drives the high-margin business of ads
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0 The Consumer Data Revolution
The First Data RevolutionExample: Amazon.comMainly implicit data, some explicit data
The Second Data RevolutionExample: FacebookMainly explicit dataCustomers start interacting
The Consumer Data RevolutionHow the attitudes of individuals to their info is changing
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0 Focus on Interactions
Who knows about your relationships with others?How does Google (or Amazon) differ from IBM (or Microsoft)?
Past, present and futurePast Given data, get me insightsPresent Given problem, get me dataFuture: Consumer data revolution I give you data, you give me money!
FrameworkArchitectures of experimentation (Web1) Give set of possible actions, do experimentsArchitectures of participation (Web2)Architectures of interaction (Web3)
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0 Communication, Computation and Information
1970’s “Experts” learn a language the
computer understandsDigitizing back office10M people
1980’s Front office interacts with back
office100M people
1990’s Customers interact with firmSearch: 1bn people poking at stuff
2000’s1bn people poking at stuff100M people producing stuff Peer-production and collaboration Customers interact with customers
NowDiscovery in addition to search Serendipity: Discover what not
searched People in addition to pages Social commerceMobile in addition to PC (and paper) Continuous partial attentionModel current situation plus history Sensing
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0 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
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0 Why do people visit? 为何访问网站
35%
Research: Response indicates having a target or topic for which customer wants to gather information in depth 搜索：抱着某种目标或主题，想深入收集一些信息（如“寻找关于智利的书籍”）
31% Browse: Looks at items casually at a more general level than Research浏览：比搜索要低一个层次，更随意地浏览一些信息（如“看看音乐 / 书籍方面的信息”，而没有特指）
16% Buy: Response indicates intent to buy in this visit (“buy a book”)购买：访问网站是想购买（如“买一本书”）10% Complain: Complains about some feature of the site抱怨：抱怨对于网站有些方面的不满9% Post-buy: Mentions checking order status, other account activities购后：查询订单状态，以及其它的一些帐户活动7% Community: Mentions usage of some feature of community, like reviews交流：使用网站的一些社区功能，如论坛
7% Price: Mentions getting information about price for specific items (does not include “looking for deals” Browse)询价：查询一些特定商品的价格信息（不包括“找找看看有没有要买的东西”——这属于浏览）
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0 Why do people visit? 人们为什么访问网站？
2.9% Goldbox: Mentions Goldbox activity百宝箱活动：进行百宝箱活动2.2% Gift: Indicates looking for a gift for someone else礼物：为其他人找一些礼物2.0% Sell: Mentions a selling activity出售：从事一些卖出活动1.4%
Personalization: Mentions personalization feature (e.g., recommendations)个性化的回复：一些个性化的东西（如提建议）
0.8% Used: Mentions finding or transacting a used item二手交易：求购或者出售一些二手东西
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0 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
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0 Let Amazon.com access your camera and microphone?
November 2007Adobe Flash installed on 820 million Internet-connected computers and mobile devices
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0 Integrated Media Measurement Inc
•IMMI Listening into
your roomevery 30 seconds,for 10 seconds.
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0 Data at the heart of the Digital Networked Economy
ClicksMusicDating
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0 Give data to get data about applicants (JobScore)
Use information about candidates from interviews at other companies
加入购物车
去收银台等一下！再加 16.01美元就能……
加入购物车
戴维斯的专辑
Also want to make recommendations!添加推荐 !
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0 Also want to make recommendations!添加推荐 !
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
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
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0 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%
All customers所有消费者 Existing customers现有消费者Cart-adds from 2nd
page: 从第二页起新购商品数量：+0.6%
Cart-adds from 2nd page:从第二页起新购商品数量：
+0.8%
Wishlist-adds: 选择礼物清单： +1.4%
DVD Cart-adds: 新购 DVD ： +0.8%
DVD (USD): +1.1% DVD (USD): +1.0
%
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0 Communication
Sources Metrics ApplicationsCollect Wall Street Trading models “Idea”Experiment Clicks Company centric E-businessContribute Profile User centric Me-businessInteract Links Relationship
centricWe-business
Recommendations ConversationsCollect Expert -Experiment Algorithm Targeting/ PushContribute Situation Discovery/ PullInteract Social Genuine
conversations
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0 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)
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0 Buy and trade business cards (Jigsaw)
7M business cards (2007.12)200k membersCommunity corrects
Loss of control
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0 Where do people go for information?
20 years ago: Produced newsPublicized opinion
10 years ago: SearchSearch: Already know what you are looking forDiscovery: Find something you didn’t know you were looking for (Serendipity)Blogs, Wikipedia
Now: Social networkDiscover via people you are connected to“Generation C”
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0 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 family80% of all consumer decisions are influenced by word-of mouth89% 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 attitudesWord-of-mouth is 4X as effective as personal selling in influencing consumers to switch brands
Context
RecipientContent
Viral Marketing works well because context, content, and targeted individual (recipient) are chosen by a friend
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0 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 dataImplicitly generated data (traces) ExperimentsUsers contribute data Incentives Data about themselves, about others, about relationships (not binary)Users expect value for themselves
© people & data | www.weigend.com Andreas S. Weigend, Ph.D. 韦思岸教授
Thank you!
Andreas Weigend+1 (650) 906-5906
www.weigend.comwww.weigend.com/blog
