San Francisco, CA 03 May 2010 Andreas Weigend @aweigend www.weigend.com 3 Decades of Innovation 1990’s: Search - find 2000’s: Social - share 2010’s: Mobile - create How the Social Data Revolution Changes (Almost) Everything Social Data Revolution • How do we “utilize” the “community”? • Who do we listen to? • Who do we co-create with? – – – – Physical friends Peers (similar properties to you) Ad hoc (e.g., for car purchase) Experts (what bestows authority?) • Institution? Past action? • Reputation/ brand as shortcut to allocate attention Social Data Revolution In the last minute • 4,000,000 search queries, • 500,000 pieces of content shared on FB, • 100,000 product searches on Amazon.com, • 40,000 bit.ly urls created, • 40,000 tweets sent Data creation and sharing Who creates data? Data is the digital air in which we breathe How will this data be used? Improve product design, service delivery, relationships How will this data be shared? Every company is a publishing company What (if anything) does it mean to “own” data? 1800’s: Transport energy Industrial Revolution 1900’s: Transport data Information Revolution 2000’s: Create and share data Social Data Revolution private public Blippy: Sharing purchase info Case study: weigend.com/blog Social: Distributed to FB friends Compare FBconnect on blog with traditional contact box (no social element) Connecting Computers Connecting Pages Connecting People Underlying? Data The amount of data each person creates doubles every 1.5 … 2 years □ after five years x 10 □ after ten years x 100 □ after twenty years x 10000 1 billion connected flash players 40 billion RFID tags worldwide Pay-as-you-drive car insurance (GPS) 99% DNA overlap Time Scales Data, Technology: ~1 year Social Norms: ~10 years Biology: ~100k yrs How the Social Data Revolution Changes (Almost) Everything Purpose of communication: to transmit information? Or is information just an excuse for communication? Web 0 Computers Web 1 Pages Data Web 2 People Introduction Data I C2B (Customer-to-Business) II C2C (Customer-to-Customer) III C2W (Customer-to-World) IV Insights v Questions Part I: C2B +1 800-4-SCHWAB Imagine... You knew all the things people here have bought You knew all of their friends You knew their secret desires ... what would you do? Decision making Discovery Recommendations …but people want to discover and help with decisions! Google helps people find stuff Amazon.com helps people make decisions… …based on reviews C2B Data Strategy: - Reviews - Purchases, Clicks… Customers who bought this item also bought… Customers who viewed this item also viewed… Customers who viewed this item ultimately bought… Amazon.com helps people make decisions… … based on clicks and purchases creating and refining product space awareness… Process of Shopping? … only occasionally punctuated by purchases How do you know peoples’ secret desires? Accounting Amazon.com is engineered for feedback Data Sources Attention Transactions Clicks Intention Search Context Geolocation Device The Social Graph Connection data New phone product: How to market? Traditional segmentation Demographics Loyalty Connection data Who called whom? 1.35% Adoption rate 4.8x 0.28% Traditional segmentation Connection data Business Customers Part II: C2C C2C = Customer-to-Customer Customers share with each other Amazon.com Share the Love Amazing conversion rates since you chose: Content (the item) Context (you just bought that item) Connection (you ask Amazon to email your Conversation (information as friend) excuse for communication) Blippy: Sharing purchases Social network intelligence Fraud reduction – Provide risk scores Social graph targeting Provide list of prospects Influencer Marketing? Real life vs Market to influential people… … and then reach everyone else for free Chain length Real Life 38% ≥ 4 links Facebook 86% ≥ 4 links C2W Part III: Amazon.com: Public sharing of interests Consumers - Engage - Share - Connect 3 times per week “We are not in the business of keeping the media companies alive.” Trevor Edwards Nike Corporate Vice President for Brand and Category Management “We are in the business of connecting with consumers.” Q: Or rather in the business of facilitating consumers to connect with each other? • Search tweets • Create tweets • Follow users http://www.mrtweet.com The Illusion of an Audience Part IV: Insights = + wheels = + heels Customer Product Brand From controlled production for the masses… … to uncontrolled production by the masses = Shift in Customer Expectations People trust reviews and comments by others more than marketing messages People use their friends’ attention to filter information and to discover new things Social filter Corner / Oversized Rooms: Rooms Ending in: 04 Oversized, Corner Room, Quiet Room 24 Oversized, Corner Room with North Times Square Views (Higher Floors are Preferred Rooms to Avoid: Rooms Ending in: 01, 21 Possible Ice Machine / Elevator Noise 08, 17 Limited View Rooms Part V: Questions Outline: Intuit Questions Data creation and sharing Consumer expectations Innovation methodology Marketing in SDR The 4 C's of marketing E-business Me-business We-business Monetization Data creation and sharing Who creates data? Data is the digital air in which we breathe How will this data be used? Improve product design, service delivery, relationships How will this data be shared? Every company is a publishing company What (if anything) does it mean to “own” data? Consumer expectations How have consumer expectations changed towards creating, sharing, accessing, and controlling data, especially in the financial area? • What benefits will customers expect in exchange to giving Intuit permission to use their data? Ultimately, how can Intuit help people discover products and services, make better decisions, and subsequently participate in the value its customers create? Innovation methodology How should Intuit experiment with C2C platforms for social commerce, such as Facebook? How can Intuit leverage C2W data (Customer-to-World), such as Twitter? Which new data sources and technologies should Intuit pay attention to, e.g., for recommendations? Marketing in SDR What are the obstacles for Intuit to fully utilize the data of its customers Including consumer choice, purchase decisions, social relations, attitudes and beliefs? How can the limitations of traditional market research be overcome by "instrumenting the world“? I.e., by systems and incentives that enable customers to give feedback to Intuit whenever they want to? How can Intuit marketing leverage the consumer mind shift of the social data revolution? The 4 C’s of Marketing Content Context Connection Conversation E-biz Me-biz We-biz Who talks to whom? Consumers to consumers Who trusts whom? Shift from institutions to individuals Who is in control? From e-business (company focus, Web 1.0) to me-business (customer focus , Web 2.0) to we-business (community focus , Web 3.0) Monetization Who manages whom? Move from CRM to CMR (Customer Managed Relationships) Who pays whom? Design incentives for participation and interaction Charge as much as you can Charge as little as you can? • Jeff Jarvis Transaction economy Relationship economy • Shoshana Zuboff Summary Innovation Internal External • “Most smart people don’t work here.” Bill Joy Data Collect and analyze Create and share Experiments Push and prey Launch and learn Q&A Andreas Weigend @aweigend www.weigend.com http://weigend.com/blog @aweigend OPEN DATA is part of the OPEN FIRST group. Ted Shelton. Noreena Hertz. Doc Searls. Andreas Weigend. Research focused into how mobile – global – cloud impacts the organizations of the future. OPEN DATA helps companies: Understand the value of the data they already have, and to Show them how to create significant additional value by combining these data with appropriate other data Example: Publishing the right data in order to benefit Customers and trading partners, and Third party developers.