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The Unrealized Power of Data Andreas Weigend people & data

Predictive Analytics World San Francisco , February 19, 2009. The Unrealized Power of Data Andreas Weigend people & data. Outline. Q: Current bottleneck for you in your business? (Scarce vs abundant)? Historical perspective Business, Data and Communication Current trends

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The Unrealized Power of Data Andreas Weigend people & data

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  1. Predictive Analytics WorldSan Francisco, February 19, 2009 The Unrealized Power of DataAndreas Weigendpeople & data

  2. Outline • Q: Current bottleneck for you in your business? (Scarce vs abundant)? • Historical perspective • Business, Data and Communication • Current trends • From Transaction Economics to Relationship Economics • The Customer Data Revolution: Shift in Customer Expectations • Implications: From CRM to CMR • Customer Managed Relationships • Applications to business: Marketing 2.0 • Why predictive analytics: Relevance • How to do it: PHAME • Problem – Hypotheses – Action – Metrics - Experiments

  3. Business, Data, and Communication • 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

  4. Amount of data • Overall : About 100GB per person on the planet • Doubling every 1-2 years • Mainly user generated • Example: Youtube • 15 hours of video uploaded every minute • Example: Flash • 1bn installs

  5. My behavior • IMMI • Listening into your room • every 30 seconds, • for 10 seconds.

  6. Current trends • Market research • Combine surveys with click data • Assumption heavy  Data rich model Relation-ships Inter-actions Trans-action

  7. The Customer Data Revolution • 1. Sniffing the digital exhaust • Mainly implicit data, some explicit data • What is new? More data sources, esp. location data • 2. Individuals talk about themselves • Mainly explicit contributions • 3. Individuals reveal relationships with others • Directed, asymmetrical, multidimensional (not binary!) • The Customer Data Revolution: Shifting expectations • Attitude of individuals to their information • Economics of data

  8. Wishlist

  9. Outline • Historical perspective • Business, Data and Communication • Current trends • From Transaction Economics to Relationship Economics • The Customer Data Revolution: Shift in Customer Expectations • Implications: From CRM to CMR • Customer Managed Relationships • Customer value • E-Business  Me-Business • Who pays whom? • Applications to business: Marketing 2.0

  10. Marketing 2.0 • Broadcast  1:1 Marketing? • Social marketing • Implications for predictive analytics: redefining CLV • Intrinsic / individual • External / network component • Applications to business • Amazon’s “Share the Love”

  11. Conversations • Conversation / Communication • Between whom? Company downcasting Individuals

  12. Leverage the social graph • Example: New communications service • US phone company with deep experience with targeted marketing • Sophisticated segmentation models based on experience, intuition, and data • e.g., demographic, geographic, loyalty data • Hill, S., F. Provost., and C. Volinsky.Network-based Marketing: Identifying likely adopters via consumer networks.Statistical Science 21 (2) 256–276, 2006 • . • Response increases by a factor of 4.82 by marketing to nearest neighbors (NN) • From 0.28% based on segmentation, to 1.35% based on social graph (1.35%) (0.83%) (0.28%) (0.11%)

  13. Recommendations 2.0 • People • Friends • Specific people you know • Viral marketing • Peers • Fans (G-star) • Experts • Fashion bloggers • Data • Clicks • Purchases • Forward, tell a friend • Relationship • Annotate • Attention • Search • Intention • Location • Situation • Product data

  14. Outline • Historical perspective • Business, Data and Communication • Current trends • From Transaction Economics to Relationship Economics • The Customer Data Revolution: Shift in Customer Expectations • Implications: From CRM to CMR • Customer Managed Relationships • Applications to business: Marketing 2.0 • Why predictive analytics: Relevance • Respect • How to do it: PHAME

  15. You want to be PHAME-ous! • PHAME • Problem • Hypotheses • Action • Metrics • Experiments

  16. Summary • Historical perspective • Business, Data and Communication • Current trends • From Transaction Economics to Relationship Economics • The Customer Data Revolution: Shift in Customer Expectations • Implications: From CRM to CMR (Customer Managed Relationships) • Applications to business: Marketing 2.0 • Why predictive analytics: Relevance • How to do it: PHAME • Web: www.weigend.com • Phone: +1 650 906-5906

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