how comcast uses data science to improve the customer experience
TRANSCRIPT
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Daily pattern: views in similar hours of the days are more similar
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Weekly pattern: views in similar days of the week are more similar
Daily pattern: views in similar hours of the days are more similar
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Weekly pattern: views in similar days of the week are more similar
Daily pattern: views in similar hours of the days are more similar
Overall decay: recent views are more similar
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VOD Daypart View Similarity
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VOD Daypart View Similarity
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Repeated-Search Pattern
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Linear(Station-level) View Similarity
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Number of Signals
0.77
= New Signal
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100%
Top 5 Top 10 Top 20
Only Social
Nielsen + DVR
Nielsen + DVR +Social
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0.40 0.60 0.80 1.00 1.20 1.40 1.60
Re
call
Resolution (Weighted Sum, Normalized by User Study)
Recall vs. Resolution
BaseLine
CoMPASS
CoMPASS++
ViaccessOrca
DigitalSmith
Rovi
ContentWise
Gravity
MortarData
ThinkAnalytics
Compass (Trend)
Various internal and externalAlgorithms
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Picture courtesy of Cisco
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Baseline w/100% cachesize
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Baseline w/100% cachesize
Prediction w/30% cache size
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Baseline w/100% cachesize
Prediction w/30% cache size
Prediction w/60% cache size
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