This document outlines lecture slides from a course on big data and personalization. It discusses how segmentation of large datasets can be used to personalize services down to the individual level, and how sensors and wearable devices are generating more bodily data that can be used for personalization. It also addresses the limitations of algorithmically curated personalization, such as reduced serendipity, autonomy, and sense of community, and how some companies like Zappos are able to offer personalized customer service without relying entirely on customer data.

1. MK99 – Big Data 1
Big data & cross-platform analytics
MOOC lectures Pr. Clement Levallois

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Data & personalization

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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

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1. From segmentation to personalization
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Segmentation helps refine the picture
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from a mass of data to meaningful subgroups of data points.
•
Why not go down to extreme segmentation: segments the size of an individual?
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Major websites do it (Amazon, Yahoo!, Netflix, etc.)
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Ads providers do it (Facebook)
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News feed do it (Prismatic, Pulse)
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Advantages: pinpoint accuracy and relevance
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Inconvenient: operational costs

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Example

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Is data-based personalization too hard?
If the industry can do mass customization on hardware, this should be possible on software

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2. Beyond behavior: tracking individual bodies
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Internet of Things
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Quantified Self
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Wearable tech
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Connected objects
More sensors, more data created by or connected to individuals

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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

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The case of Nicholas Felton…

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One page from the 2012 report

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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/

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3. Curated world views
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Personalization of content = taylored experience, equated with comfort and luxury. Good!
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But negative impact on:
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Serendipity: experiencing pleasant surprise by stepping outside of one’s own habitual environment.
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The sense of belonging: the desire to part of a community, sharing similar codes and references
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Autonomy: individuals might prefer to curate their environment by themselves, and not by algorithms they don’t control.

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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/

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4. Wait! Personalizing without data?
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The Zappos case:
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A focus on customer service
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Delivered by human contact (call center in the US managed without scripting nor limit on call time)
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No insistence on data in their corporate culture (vs Amazon).
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Is data outside of the picture?
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No! Zappos does data-based personalization on their digital channels!
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But data is a supporting tool not a replacement for a great customer relationship.

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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.