MK99 – Big Data 1 
Big data & cross-platform analytics 
MOOC lectures Pr. Clement Levallois
MK99 – Big Data 2 
Data & personalization
MK99 – Big Data 3 
Data & personalization 
1. 
From segmentation to personalization 
2. 
Beyond behavior: tracking individ...
MK99 – Big Data 4 
1. From segmentation to personalization 
• 
Segmentation helps refine the picture 
– 
from a mass of da...
MK99 – Big Data 5 
Example
MK99 – Big Data 6 
Is data-based personalization too hard? 
If the industry can do mass customization on hardware, this sh...
MK99 – Big Data 7 
2. Beyond behavior: tracking individual bodies 
• 
Internet of Things 
• 
Quantified Self 
• 
Wearable ...
MK99 – Big Data 8 
Bodily measurement 
Sensor 
Company 
Product 
Picture 
Location 
Mobile phone 
Google 
Google Maps 
Mov...
MK99 – Big Data 9 
The case of Nicholas Felton…
MK99 – Big Data 10
MK99 – Big Data 11 
One page from the 2012 report
MK99 – Big Data 12 
Just N. Felton? 
“Autodesk employee Blake Menezes wears his Jawbone Up as part of a global corporate h...
MK99 – Big Data 13 
3. Curated world views 
• 
Personalization of content = taylored experience, equated with comfort and ...
MK99 – Big Data 14 
Sept 04, 2014. The Wall Street Journal reported Wednesday that Twitter is planning to debut a Facebook...
MK99 – Big Data 15 
4. Wait! Personalizing without data? 
• 
The Zappos case: 
– 
A focus on customer service 
– 
Delivere...
MK99 – Big Data 16 
This slide presentation is part of a course offered by EMLYON Business School (www.em-lyon.com). 
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Data and personalization

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Slides of the course on big data by Clement Levallois from EMLYON Business School.
For business students. Check the online video connected with these slides.
-> An exploration of the opportunities and limits that data brings to personalization.

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Data and personalization

  1. 1. MK99 – Big Data 1 Big data & cross-platform analytics MOOC lectures Pr. Clement Levallois
  2. 2. MK99 – Big Data 2 Data & personalization
  3. 3. MK99 – Big Data 3 Data & personalization 1. From segmentation to personalization 2. Beyond behavior: tracking individual bodies 3. Algorithmically curated worldviews for individuals: -> the limits 4. Personalizing without data
  4. 4. MK99 – Big Data 4 1. From segmentation to personalization • 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 costs
  5. 5. MK99 – Big Data 5 Example
  6. 6. MK99 – Big Data 6 Is data-based personalization too hard? If the industry can do mass customization on hardware, this should be possible on software
  7. 7. MK99 – Big Data 7 2. Beyond behavior: tracking individual bodies • Internet of Things • Quantified Self • Wearable tech • Connected objects More sensors, more data created by or connected to individuals
  8. 8. MK99 – Big Data 8 Bodily measurement Sensor Company Product Picture Location Mobile phone Google Google Maps Movement Arm band Nike Fuel Band Heart rate Body scale Withings Smart Body Analyzer Perspiration Wrist watch Basis Peak Sleep Under mat Withings Aura Fingerprint Mobile phone Apple iPhone 5
  9. 9. MK99 – Big Data 9 The case of Nicholas Felton…
  10. 10. MK99 – Big Data 10
  11. 11. MK99 – Big Data 11 One page from the 2012 report
  12. 12. MK99 – Big Data 12 Just N. Felton? “Autodesk employee Blake Menezes wears his Jawbone Up as part of a global corporate health challenge. Menezes keeps the activity data to himself, but other employers are exploring ways to monitor their staff's wearable devices to help keep a lid on rising health care costs.” (photo via Autodesk) Source: http://www.forbes.com/sites/parmyolson/2014/06/19/wearable-tech-health-insurance/
  13. 13. MK99 – Big Data 13 3. Curated world views • Personalization of content = taylored experience, equated with comfort and luxury. Good! • But negative impact on: – Serendipity: experiencing pleasant surprise by stepping outside of one’s own habitual environment. – The sense of belonging: the desire to part of a community, sharing similar codes and references – Autonomy: individuals might prefer to curate their environment by themselves, and not by algorithms they don’t control.
  14. 14. MK99 – Big Data 14 Sept 04, 2014. The Wall Street Journal reported Wednesday that Twitter is planning to debut a Facebook-style, algorithmically curated newsfeed. The idea of a curated newsfeed is angering many who believe that Twitter's non-interference in the content stream is a feature, not a bug. Source: http://www.washingtonpost.com/blogs/the-switch/wp/2014/09/04/why-twitters-users-are-in-open-revolt/
  15. 15. MK99 – Big Data 15 4. Wait! Personalizing without data? • The Zappos case: – A focus on customer service – Delivered by human contact (call center in the US managed without scripting nor limit on call time) – No insistence on data in their corporate culture (vs Amazon). – Is data outside of the picture? • No! Zappos does data-based personalization on their digital channels! • But data is a supporting tool not a replacement for a great customer relationship.
  16. 16. MK99 – Big Data 16 This slide presentation is part of a course offered by EMLYON Business School (www.em-lyon.com). Contact Clement Levallois (levallois [at] em-lyon.com) for more information.

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