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[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object]
Number of freely connected nodes where exchange cost is near zero
Number of freely connected nodes where exchange cost is near zero
Number of freely connected nodes where exchange cost is near zero Hyperdata Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+
Number of freely connected nodes where exchange cost is near zero Hyperdata Web2.0 Social Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+ Business analysis Services Mashups Responsive and self-configuring Responsive; ‘agents’ APML Microformats
When the network knows more than anyone
Number of freely connected nodes where exchange cost is near zero When the network knows more than anyone Hyperdata Web2.0 Social Network Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+ Business analysis Services Mashups Responsive and self-configuring Responsive; ‘agents’
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],When the network knows more than anyone
Number of freely connected nodes where exchange cost is near zero When the network knows more than anyone Hyperdata Web2.0 Social Network Phenomena Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+ Business analysis Services Mashups Responsive and self-configuring Responsive; ‘agents’ Predictive
Hypodata
“ Brain Scanners can predict a decision up to 10 seconds before a person is aware of making that decision” Nature Neuroscience, April 2008 Hypodata
“ ABSTRACTA headphone-type gaze detector for a full-time wearable interface is proposed. It uses a Kalman filter to analyze multiple channels of EOG signals measured at the locations of headphone cushions to estimate gaze direction. Evaluations show that the average estimation error is 4.4® (horizontal) and 8.3® (vertical), and that the drift is suppressed to the same level as in ordinary EOG. The method is especially robust against signal anomalies. Selecting a real object from among many surrounding ones is one possible application of this headphone gaze detector.” http://portal.acm.org/citation.cfm?doid=1125451.1125655  via  http://liftlab.com/think/nova/2006/06/09/wearable-gaze- detector-in-the-form-of-headphones/  Hypodata
Hypodata - MIT’s “Sixth Sense” http://www.flickr.com/photos/whiteafrican/3253881037/ Pattie Maes’s TED talk on MIT’s “Sixth Sense”: http://www.youtube.com/watch?v=blBohrmyo-I Mashups Responsive and self-configuring Responsive; ‘agents’
Augmented and supplemented Reality University of Washington, 2008:  http://uwnews.org/article.asp?Search=contact+lens&articleid=39094 ,[object Object],[object Object],[object Object]
Any sufficiently advanced technology is indistinguishable from magic
Nodes Open Structured Data Business Web 2.0 Social Network Phenomena Epiphenomena ESP?
“ They’re ‘doing’, not just ‘viewing’ – appropriation, not passive “use”  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
“ They’re ‘doing’, not just ‘viewing’ – appropriating the digital domain
Augmented Reality - brands and interaction http://www.metroparisiphone.com/index_en.html
The “Outernet” – Marking and spraying… http://www.junaio.com / ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
 
How will this impact digital businesses and eCommerce?
[object Object],[object Object],[object Object],[object Object],What’s the point of a store?
Obama-Preedy Pricing Principle ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Obama-Preedy Pricing Principle ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Obama-Preedy Pricing Principle ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Performance With thanks to Michael Ross, eCommera. Bad analogy is not his responsibility though... KPI type What Example Volume Feed the machine Site visitors, viewers Margin Extract maximum nutrients. Chew well. Profit per visit, per session, per episode Minimise waste Don’t dribble; don’t leave the stalks Minimise out-of-stock visits Return on capital employed Calories in > effort to eat. ie “no salad” ;) Return on inventory, return on equipment, return on staff Retention  Eat again, more easily (remember the potato patch) Customer satisfaction, order frequency, churn.
eCommerce metric Sales/Square foot?
eCommerce metric π/εs
π/εs Profit per engagement second. http://www.internetretailing.net/news/editorial-video-on-profit-per-pixel-second
π/εs Profit per engagement second. http://www.internetretailing.net/news/editorial-video-on-profit-per-pixel-second   ,[object Object],[object Object],[object Object],[object Object],[object Object]
π/εs Profit per engagement second. http://www.internetretailing.net/news/editorial-video-on-profit-per-pixel-second
Thank you
www.ianjindal.com www.internetretailing.net www.innoparticularorder.com www.europeanecommerceforum.org   http://twitter.com/ianjindal   Thank you
Making and Measuring Marketing Magic Random House Digital Afternoon London, December 2009 www.ianjindal.com Thank you

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Ps097: RandomHouse Digital Day presentation on Making Magic

  • 1.
  • 2.
  • 3. Number of freely connected nodes where exchange cost is near zero
  • 4. Number of freely connected nodes where exchange cost is near zero
  • 5. Number of freely connected nodes where exchange cost is near zero Hyperdata Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+
  • 6. Number of freely connected nodes where exchange cost is near zero Hyperdata Web2.0 Social Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+ Business analysis Services Mashups Responsive and self-configuring Responsive; ‘agents’ APML Microformats
  • 7. When the network knows more than anyone
  • 8. Number of freely connected nodes where exchange cost is near zero When the network knows more than anyone Hyperdata Web2.0 Social Network Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+ Business analysis Services Mashups Responsive and self-configuring Responsive; ‘agents’
  • 9.
  • 10. Number of freely connected nodes where exchange cost is near zero When the network knows more than anyone Hyperdata Web2.0 Social Network Phenomena Metadata Data Endodata Hypodata 0 1 3 10 100 1000s+ Business analysis Services Mashups Responsive and self-configuring Responsive; ‘agents’ Predictive
  • 12. “ Brain Scanners can predict a decision up to 10 seconds before a person is aware of making that decision” Nature Neuroscience, April 2008 Hypodata
  • 13. “ ABSTRACTA headphone-type gaze detector for a full-time wearable interface is proposed. It uses a Kalman filter to analyze multiple channels of EOG signals measured at the locations of headphone cushions to estimate gaze direction. Evaluations show that the average estimation error is 4.4® (horizontal) and 8.3® (vertical), and that the drift is suppressed to the same level as in ordinary EOG. The method is especially robust against signal anomalies. Selecting a real object from among many surrounding ones is one possible application of this headphone gaze detector.” http://portal.acm.org/citation.cfm?doid=1125451.1125655 via http://liftlab.com/think/nova/2006/06/09/wearable-gaze- detector-in-the-form-of-headphones/ Hypodata
  • 14. Hypodata - MIT’s “Sixth Sense” http://www.flickr.com/photos/whiteafrican/3253881037/ Pattie Maes’s TED talk on MIT’s “Sixth Sense”: http://www.youtube.com/watch?v=blBohrmyo-I Mashups Responsive and self-configuring Responsive; ‘agents’
  • 15.
  • 16. Any sufficiently advanced technology is indistinguishable from magic
  • 17. Nodes Open Structured Data Business Web 2.0 Social Network Phenomena Epiphenomena ESP?
  • 18.
  • 19. “ They’re ‘doing’, not just ‘viewing’ – appropriating the digital domain
  • 20. Augmented Reality - brands and interaction http://www.metroparisiphone.com/index_en.html
  • 21.
  • 22.  
  • 23.  
  • 24. How will this impact digital businesses and eCommerce?
  • 25.
  • 26.
  • 27.
  • 28.
  • 29. Performance With thanks to Michael Ross, eCommera. Bad analogy is not his responsibility though... KPI type What Example Volume Feed the machine Site visitors, viewers Margin Extract maximum nutrients. Chew well. Profit per visit, per session, per episode Minimise waste Don’t dribble; don’t leave the stalks Minimise out-of-stock visits Return on capital employed Calories in > effort to eat. ie “no salad” ;) Return on inventory, return on equipment, return on staff Retention Eat again, more easily (remember the potato patch) Customer satisfaction, order frequency, churn.
  • 32. π/εs Profit per engagement second. http://www.internetretailing.net/news/editorial-video-on-profit-per-pixel-second
  • 33.
  • 34. π/εs Profit per engagement second. http://www.internetretailing.net/news/editorial-video-on-profit-per-pixel-second
  • 36. www.ianjindal.com www.internetretailing.net www.innoparticularorder.com www.europeanecommerceforum.org http://twitter.com/ianjindal Thank you
  • 37. Making and Measuring Marketing Magic Random House Digital Afternoon London, December 2009 www.ianjindal.com Thank you