Economics of Shared Data Plans Soumya Sen Carlee Joe-Wong Sangtae Ha

Issue: Sustainability e-commerce cloud services m-commerce Google Amazon Apple Microsoft Facebook wired wireless AT&T Verizon T-Mobile Sprint Comcast

Issue: Demand Growth

Issue: Viability Spectrum Crunch 108% Growth Data Caps

Trends: Pricing Evolution

Trends: Shared Data Plans

Perspectives & Questions Is a shared data plan always better? How to fairly share data across users? How to price shared data plans? How many shared plans to offer? Consumers Service Providers

Shared Plans Device 1Device 2 Entertainment & Productivity device Child’s & Parent’s device

Shared Plans Devices have different marginal value for consumed bandwidth (v 1, v 2 ) Usage distribution: f i (c i ), demand c i Different max usage (C 1 max, C 2 max ) Device 1Device 2

Shared Plans Entertainment & Productivity device – v 1 C 2 max Child’s & Parent’s device – v 1 < v 2, C 1 max < C 2 max Device 1Device 2

Shared Data Plan Pricing Per device fee (by device type): g 1, g 2 Bandwidth Caps: B 1, B 2, B s Tiered (approximates usage pricing $10/GB): – {p 1, p 2 } < p s (in $/GB up to cap) Overage fees: { o 1, o 2 } < o s (in $/GB above cap) DevicesMonthly Line Access (per device) Smartphones$40 Basic Phones$30 Jetpack/Netbooks/Notebooks/USBs$20 Tablets$10

Overage Scenarios Demand loss above cap Quality degradation, throttling above cap Self-restraint by users on lower utility device α of overage demand is lost Usage loss from lower valued (v 1 ) device

3- Stage Model Assumptions (relaxable): Continuum of data caps to choose from Log utility function: U i =v i log(1+c i )-p i B i Choose between shared and individual Data plans Choose the data cap for the chosen plan Adjust for usage loss (if needed) and incur overage fees Demand for data on each device is realized Direction of solution

Analysis: Individual Data Plans Compute (B 1 *, B 2 * ) and (U 1 *, U 2 * ) User utilities: Expected utility:

Analysis: Shared Data Plan (1) Relationship between data cap, realized demand, and usage loss in overage regime c2c2 c1c1 (c 1, c 2 ) Case 2: No demand loss c2c2 c1c1 (c 1, c 2 ) Demand loss Case 1: c2c2 c1c1 (c 1, c 2 ) Demand loss Case 3:

Analysis: Shared Data Plan (2) Shared plan allows adjustments across devices Compute B s *, U s * in each region and select the best option Use E(U s * ), E(U 1 * +U 2 * ) to choose shared vs individual data plans

Example Usage Stats 19 iPhone, 15 iPads iPad users: β~(0.348, 0.408) iPhone users: β~(0.515, 0.191)

Consumer Choice: Non-trivial Indv. Share d Correct choice of shared or individual plan depends on demand loss in overage regime due to behavioral factors (user’s self-restraint) and technological factors (performance degradation from throttling)

Robustness: Tiered Data Plans Consumer choice can be even more complicated for tiered data plans Indv. Share d The budget choices are B 1 = 0.2, 1 and B 2 = 0.5, 1.5 (in GB)

Future Directions Is a shared data plan always better? How to fairly share data across users? How to price shared data plans? What shared data caps to offer? Consumers Service Providers

“Fair” sharing Build “fairness” into the system Allow “priorities” Use dynamic planning to increase “efficiency” Alice Bob Chris

Empowering Consumers Daily allocation by users + Usage alerts Fair allocation by apps + Usage alerts Set cap. Set priority. priority=1Priority=2 Chris Alice

Trial App GUIs Personal Usage MonitoringShared Usage MonitoringShared Usage Prediction

Trial Logistics Control GroupTrial Group Priority = 1 Priority = 3 Priority = 2 2 GB All vie for the same cap No prioritization No dynamic fair usage division No control on app usages Fair usage division App usage monitoring

References Innovating Access Pricing – Industry-academia collaboration – SDP 2013 (Workshop on Smart Data Pricing) – co-located with IEEE INFOCOM 2013, Turin, Italy DataWiz (free iOS & Android mobile app) – scenic.princeton.edu/datawiz/ Questions? Thank you!