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Soumya Sen, WITE 2012 1
Smart Data Pricing (SDP)
Soumya Sen
Joint Work with: Sangtae Ha, Carlee Joe-Wong, Mung Chiang
Innovating Data Plans
Soumya Sen, WITE 2012 2
?
Challenges to the Internet
1
10
100
feasible
economicallyviable
Is it
year
/GB$
%technologically
sustainable
to keep the Internet
&
?
?
Soumya Sen, WITE 2012 3
Challenges to the Internet
feasible
economicallyviable
Is it
1
10
100
year
/GB$
%technologically
sustainable
to keep the Internet
&
?
Technologicalfactors
Humanfactors
Economicfactors
Soumya Sen, WITE 2012 4
feasible
economicallyviable
Is it
technologicallysustainable
to keep the Internet
&
?
Technologicalfactors
Humanfactors
Economicfactors
Network Economics
NetEcon as a SolutionChallenges to the Internet
HCI,Engineering
ConsumerBehavior
Economics
Systems
UserTrials
Theory
Tools Methods
Soumya Sen, WITE 2012 5
Network Economics
NetEcon: A Holistic Agenda
Technology
HCI & Analytics
Soumya Sen, WITE 2012 6
What is Smart Data Pricing (SDP)?
A. Usage pricing/metering/throttling/capping
B. Time/location/congestion-dependent pricing
C. App based pricing
D. Smart Markets, Sponsored content
E. Paris metro pricing
F. Quota-aware content distribution
G. All of the above…
Time-Dependent Pricing
Soumya Sen, WITE 2012 7
NetEcon as a SolutionThe Driving Forces
Soumya Sen, WITE 2012 8
Evolution of Access PricingThe Driving Forces
Soumya Sen, WITE 2012 9
Time Elasticity
Time Elasticity
Volu
me
Streamingvideos,Gaming
Texting,Weather, Finance
Email,Social
Network updates
Cloud
SoftwareDownloads
Movies & Multimedia downloads,
P2P
Opportunities
Large Peak-Valley Differential
Opportunities forExploiting time-elasticity
of demand
Soumya Sen, WITE 2012 10
Stakeholder Perspectives
• Consumers• Policy feasibility• Industry moves: US, Europe, India, Africa
Soumya Sen, WITE 2012 11
Time Dependent Pricing (TDP)
ISP cost optimization, taking user reaction into account
Soumya Sen, WITE 2012 12
ISP’s Optimization ProblemCost of
overshooting capacity
Cost of rewards
Soumya Sen, WITE 2012 13
Estimating Waiting FunctionEconomic modeling
reward
patience indexdelay
waiting function
Soumya Sen, WITE 2012 14
TDP Architecture
Soumya Sen, WITE 2012 15
Princeton Trial
• TDP for 3G data – Feasibility study
• Prototype development
• Trial • 50 volunteers
Data Flow
Money Flow
Soumya Sen, WITE 2012 16
Graphical User Interfaces (GUIs)– Price display
• Day-ahead • Color coded: red (<10%), orange (10 ~19%),
yellow (20 ~ 29%) and green (>= 30%)
– Self-education• Top 5 Apps
– User control• Autopilot mode
Soumya Sen, WITE 2012 17
Price Sensitivity
• Do users wait to use mobile data in return for a monetary discount?– Average usage decrease in high-price periods relative to the changes in
low-price periods
Usages changed by -10.1% in high-price and 15.7% in low-price periods
Soumya Sen, WITE 2012 18
Notification Effectiveness
• Do notifications impact usage?– About 60-80% of the active users decrease their
usage in response to price notification pop-ups
Soumya Sen, WITE 2012 19
UI Effectiveness• Do users respond more to the numerical values of TDP prices
or to the color of the price indicator bar on the home screen?
Soumya Sen, WITE 2012 20
Optimized TDP Impact• Does the peak usage decrease with time-dependent pricing? And does this
decrease come at the expense of an overall decrease in usage?– Optimized TDP reduce the peak-to-average ratio– Overall usage significantly increase with TDP
30% PAR reduction
Soumya Sen, WITE 2012 21
Impact on Ecosystem
• Does the application usage distribution change due to TDP?– People are motivated to use more bandwidth during low-price
periods, “valley filling”.
Soumya Sen, WITE 2012 22
Viability
• Will you be able to decide on “when” to use?– “I think it's a great idea, ..the iPads would say, 'If you wait a
half an hour, you can have...' I thought that was incredibly useful. And I would be able to make that decision.”
• Are there apps for which you usually wait?– “[I]f I'm out in my car and I needed it for GPS, I wouldn't care
how much money I'm spending… if I just wanted to be on a social network or check my email, I would certainly wait.”
Soumya Sen, WITE 2012 23
Usefulness
• What are your main concerns with TDP?– “If it's predictable, yes, I think so, because let's say I know that
definitely everyday from 9 to 10 it's less, then I can plan a little bit.”
• Was the color-coded notification bar useful to you?– “I group the colors I would see if it's a good color for me...
because I couldn't always figure out what it meant in terms of the dollar amount and translate that into how much I was using”
Soumya Sen, WITE 2012 24
Opinions
• Were you tempted to use more data when the discounts were higher?– “[laughs] Kind of! But that also goes toward my personality of if it's on sale
I must buy it!”
• Will TDP adversely affect high-bandwidth app developers? – “I don't think this will result in those kinds of applications being developed
less, and I think that's because you're giving users the option”
Soumya Sen, WITE 2012 25
Prototypes and Trials
Soumya Sen, WITE 2012 26
Soumya Sen, WITE 2012 27
From $10/GB To SDP• Real progress feasible
– http://www.datami.com
• Collaboration will help – http://scenic.princeton.edu/SDP2012/
• Get to win-win for all
References:
• S. Sen, C. Joe-Wong, S. Ha, M.Chiang, “Incentivizing Time-Shifting of Data: A Survey of Time-Dependent Pricing for Internet Access”, IEEE Communications Magazine, Nov. 2012.
• S. Ha, S. Sen, C. Joe-Wong, Y. Im, M. Chiang, “TUBE: Time Dependent Pricing for Mobile Data”, ACM SIGCOMM 2012.
• S. Sen, C. Joe-Wong, S. Ha, J. Bawa, “When the Price is Right: Enabling Time-Dependent Pricing of Broadband Data,” ACM SIGCHI 2013.
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