last modified: 2018-07-02
Segmentation helps refine the picture from a mass of data to meaningful subgroups of data points.
Why not go down to extreme segmentation: segments the size of an individual?
Major websites do it (Amazon, Yahoo!, Netflix, etc.)
Ads providers do it (Facebook)
News feed do it (Prismatic, Pulse)
Advantages: pinpoint accuracy and relevance Inconvenient: operational complexity
A list of bodily aspects being measured with examples:
Samsung, Apple, etc.
Weight, heart rate
Behavior in public areas
A description of how AGT monitors large audiences in public events (click on the pic for the full document):
image::agt-2.png[AGT services for crowd management]"][align="center", title="source: https://www.agtinternational.com/wp-content/uploads/2014/10/AGT_AAG_MegaEvent-02Oct2014-2.pdf == !
Video showing how Placemeter monitors pedestrian traffic:
Nicholas Felton is a designer and data artist who produced printed annual reports from 2005 to 2014.
These reports synthesize his bodily data and social life, which he measures constantly during the year. This practice (pushed to the extreme in this case) belongs to the quantified self movement.
Insurance companies are interested in boosting individual health, using connected objects as monitoring devices
Companies are looking to provide a 360 degree solution to health and well being through constant monitoring:
Monitoring on health is also a B2B market to achieve "corporate welfare". See Nokia’s brochure on the topic of health services.
These technologies open a vast number of issues: from data privacy to the redefinition of well-being, and the grey boundary between monitoring and surveillance.
A full session of this series is devoted to discussing these issues.
For the moment, let us just repeat cautionary remarks already mentioned in a different session:
Companies rated with the customer service do personalization differently: with humans.
See how Zappos offers a great service to their customers:
or see (in French) how Trainline makes its customers happy.
Find references for this lesson, and other lessons, here.
This course is made by Clement Levallois.
Discover my other courses in data / tech for business: https://www.clementlevallois.net
Or get in touch via Twitter: @seinecle