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Data ; Algorithmes et marketing
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Transcript of Data ; Algorithmes et marketing
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Platforms, big data and marketing
Christophe BenaventUniversité Paris Nanterre
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foreword
● A deep dive in the platform world● A threefold lesson :
– Competitive advantage come from capability to coordinate a very large number of people coming from different market sides
– Datas and algorithms are the core tools
– It's not a question of knowledge, it's about how to drive behaviors to benefit more from market externalities.
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Challenges
● Consumer (brand) to customer (category)● Data integration → DMP ● Marketing automation → customer (multi
scales) journeys● Actions more than insights :
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Data is a (multi) process and one thousand of them could make noise
Acquisition Preparation Modeling Diffusion
● CRM and accounts● Social networks● Tracking (web,
retargetting...)● Buttons● Beacons ● Apps (ie shopping
list, loyalty apps)● IoT ( balance,
fridge, fitbit)● Domestic assistant● Cars and computer● API● ...
● Matching/fusion● Quality control● Big data - nosql
● Numerical● Text● Pictures● Signals
● Surveys● Scoring● Dashboards● Ranking● Electronic labels ● ...
● Traditionnal marketing survey (CA,MDS, cluster...)
● Avanced econometrics
● Network analysis● First generation of
ML● Deeplearning
A need for data architecture
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So simple ! the data scientist workshop
(twitter content topic analysis)
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Hedonometering with social content
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At the beginning a cookie
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Apps interaction
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The rise of Data Management Platforms
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Ranking : far over satisfaction measurement
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The performative biases
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Pay How You Drivebehavioral monitoring with IoT ?
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Iot : a dream of general feed back
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AB testing – the criticized Facebook experiment
Done on a ~= 700 000 indswithout asking for consent.
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Flickr : labelling with deep learning for searchable (and monetization) pics
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Meta data and derived data
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Surge Pricing : smart pricing
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For food
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Perspectives
● Retailers are cornerstone of data strategy.● How to be embedded in the data plaforms
network ?● RGDP : data privacy, portability, how much data
are personal ? How to be “data loyal”.● Health, fitness, hedonism and food ethics :
different brand/segment models.