The report published a major study into the viability and potential scale of over 25 forms of "non-neutral" mobile broadband & Internet business models.
2014 has seen huge shifts around the concept of Net Neutrality - the FCC has revealed details of new proposals, while the European Parliament voted for a harder version of neutrality than many in the telecoms industry wanted. Chilean regulators have blocked new "zero-rated" apps from mobile data plans, while Singapore's government stopped operators from trying to "tax" so-called OTT messaging players.
Lobbyists, activists and the wider telecoms and web industries are flooding the media and blog/twitterspheres with commentary, opinion and predictions of what might happen if Net Neutrality is/isn't enforced. Questions, rumours and myths about what may happen, if mysterious and vaguely-defined "Specialised Services" are permitted over broadband networks. Many observers have confused peering deals (eg Comcast/Netflix) with QoS-prioritised services, even though that is an entirely different issue.
But a deeper set of questions is being overlooked:
- What are the possible outcomes for mobile network operators in a world, where discrimination of data traffic on the basis of price or QoS is permitted?
- What are the realistic use-cases that might get applied?
- Who might pay for what services or capabilities?
- What is already happening in markets with more relaxed laws?
- Can "two-sided business models" work in mobile broadband?
- Will operators be able to charge users "per-application"?
- Net neutrality, the FCC and Title II
- New services, vendors & “monetisation” angles
- Encryption effect: DPI goes dark, Google wins?
- - What is happening? What are the implications?
- - The politics – IETF, OWA, GSMA, Google etc
- Apple SIMs
- Peering and interconnect
- User-driven policy management
- Revised & extended market model
- - Geographic regional trends
- - Overall non-neutral market forecasts
Main 2014 Report
- Why non-neutrality is an issue for mobile operators
- Major practical challenges to creating non-neutral models
- Analytical frameworks for assessing new models
- Forecasts & recommendations
Mobile broadband & Internet: Market dynamics:
- Mobile Internet vs. mobile data
- History and the emergence of Mobile Internet
- Mobile data & Internet market size & penetration
- Mobile Internet access: implications for operators & vendors
- Developed-market saturation
- Two-sided business models for mobile data/Internet P
- Traffic growth & congestion
- The "OTT threat"
- Neutrality: relevance, regulation & controversy.
- Net Neutrality defined
- Disruptive Analysis house view: avoiding confirmation bias
- The main arguments
- 2014: Regulatory turmoil & status update
- US Net Neutrality developments
- What is a "specialised service"?
Non-neutral broadband: Generic challenges.
1. No clear definition of "an app" or "service" Multi-app experiences. Partial-app experiences.
2. Business Model Fit International challenges.
3. Apps' data usage is device-dependent
4. Devices, OSs & QoS / non-neutrality
5. HTML5 changes the game again
6. Poor fit with WiFi use and femtocell offload
7. OSS/BSS challenges
8. Pricing, selling & marketing non-neutrality
9. Network dependencies & standards
10. Arbitrage & other unintended consequences
11. Mobile broadband is not like fixed
12. Organisational challenges in service providers
Main models for non-neutral mobile broadband:
- Analytical framework
- Application-specific charging & packages
- Single-app packages.
- Traffic class (eg video)
- App group/class packaging
- User-defined packages: Multi-app packages & "favourite" apps.
- Sponsored data / 1-800 data
- Reverse-billed advertising
- Sponsored websites / web-apps
- 1-800 / tollfree apps.
- Enterprise & BYOD
- Telco-OTT applications
- Bundled paid apps
- Bundled free apps
- Free service & support data
- Specialised services / QoS "fast lane"
- Venue-based services & applications.
- Managed enterprise broadband
- Public safety
- Mobile IPTV / Video
- M2M / IOT
- Web/App Acceleration
- Impeding & blocking / QoS "slow lane"
- Unenforced terms & conditions
- Blocking & throttling
- Parental Control
- Deliberate degradation
- User-defined throttling / prioritisation
- MVNO / wholesale offers
- The "Kindle model"
- Differentiated MVNOs
- Other / miscellaneous approaches
- Content modification.
- Customer-centric prioritisation
- CDNs and paid-peering
- The insurance-premium model
Forecasts, conclusions & recommendations
- Market forecasts: How much revenue from non-neutrality?
- Can two-sided business models work?
- Recommendations for mobile operators
- Recommendations for content & application providers
- Recommendations for regulators
- Recommendations for network/software vendors
- Recommendations for investors
- Recommendations for industry bodies, lobbyists & activists
LIST OF FIGURES
Figure 1: Mobile data & Internet access revenues, worldwide, 2012-2019
Figure 2: Existing mobile Internet access market vs. new non-neutral models
Figure 3: New non-neutral mobile broadband models - growth & segmentation
Figure 4: Mobile data includes both Internet access & other applications
Figure 5: Mobile data & mobile Internet timeline
Figure 6: Mobile data & Internet access revenues, worldwide, 2012-2019
Figure 7: Post-paid & pre-paid mobile Internet users, worldwide, 2012-2019
Figure 8: Prepay/postpay split by global region, 2012
Figure 9: Post- & pre-paid mobile Internet access ARPU, worldwide, 2012-2019
Figure 10: Mobile Internet/data access revenues, worldwide, 2012-2019
Figure 11: Mobile operators have many groups building data business models
Figure 12: Policy-management vendors' use-cases are proliferating
Figure 13: GSMA view of addressable market for mobile data
Figure 14: Two-sided telecoms business models are appealing, in theory
Figure 15: Data traffic growth driven by # of users to a large extent
Figure 16: Data growth in developed markets is linear not exponential
Figure 17: OTT apps extend the market, rather than compete directly
Figure 18: Networks may block ports/functions - eg SSL on WiFi hotspot
Figure 19: What is an app, and who is responsible for its data use?
Figure 20: Complexity - Multi-app user journey but a single "experience"
Figure 21: Multifunctional apps & mashups will need "partial toll-free"
Figure 22: Can mobile apps request QoS or give performance needs?
Figure 23: WiFi is multi-stakeholder & not controlled by MNOs
Figure 24: Example of a proposed "sponsored connectivity" architecture
Figure 25: Complexity of 3GPP standards relating to policy-control
Figure 26: Globe application-specific pricing example
Figure 27: Movistar Colombia application-group pricing example
Figure 28: User-selected app-based data plan (illustrative)
Figure 29: Sponsored advertising content on in-flight WiFi
Figure 30: Countries with free Wikipedia Zero mobile access
Figure 31: Facebook is pushing hard for zero-rating
Figure 32: Many countries & mobile operators block or throttle P2P traffic
Figure 33: Some operators offer fine-grained parental content control
Figure 34: Various device vendors form or partner MVNOs for bundled data
Figure 35: Device-bundled data example from Macheen
Figure 36: Example architecture for private network/MVNO roaming
Figure 37: Example of web-browser overlay data
Figure 38: CDNs / ADNs target the "middle mile", not the "neutral" last-mile
Figure 39: Internet peering and transit
Figure 40: Existing mobile Internet access market vs. new non-neutral models
Figure 41: New non-neutral mobile b-band models - growth & segmentation
Figure 42: Non-neutral mobile data models - 1 vs. 2-sided segmentation
LIST OF TABLES
Table 1: Selected examples of non-neutral mobile data models, mid-2014
Table 2: Analytical framework for non-neutral models
Table 3: Overall mobile data market inc. Internet, SMS & VAS, 2012-2019
Table 4: Global mobile data access users, prepay/postpay/M2M, 2012-2019
Table 5: Global mobile data access revs, prepay/postpay/M2M, 2012-2019
Table 6: Key arguments for and against Net Neutrality
Table 7: Analytical framework for non-neutral models
Table 8: Key success criteria for single-app subscription models
Table 9: Forecast users & revenues for "single-app" mobile data, 2012-2019
Table 10: Key success criteria for "traffic class" business models
Table 11: Forecast users & revenues for "traffic class" mobile data,
Table 12: Key success criteria for "app class" business models
Table 13: Forecast users & revenues for "app class" mobile data, 2012-2019
Table 14: Key success criteria for data proxy-based business models
Table 15: Key success criteria for "favourite apps" business models
Table 16: Forecast users & revs for "favourite apps" mobile data, 2012-2019
Table 17: Key success criteria for sponsored advert data business models
Table 18: Forecast users & revs for "sponsored advert data", 2012-2019
Table 19: Key success criteria for sponsored website data business models
Table 20: Forecast users & revs for "sponsored web" mobile data, 2012-2019
Table 21: Key success criteria for toll-free/1-800 mobile app business models
Table 22: Forecast users & revs for "toll-free/1-800 apps" models, 2012-2019
Table 23: Key success criteria for sponsored BYOD data business models
Table 24: Forecast users & revs for "sponsored BYOD" mobile data, 2012-2019
Table 25: Forecast users for "zero-rated apps" mobile data, 2012-2019
Table 26: Key success criteria for zero-rated TelcoOTT app business models
Table 27: Key success criteria for zero-rated bundled paid app/content models
Table 28: Key success criteria for zero-rated bundled free app/content models
Table 29: Key success criteria for zero-rated service/support app biz models
Table 30: Key success criteria for public-venue specialised service models
Table 31: Forecast users & revs for "public venue" specialised svcs, 2012-2019
Table 32: Key success criteria for "business class" priority data biz models
Table 33: Forecast users & revs for "business class" priority data, 2012-2019
Table 34: Key success criteria for public safety priority data biz models
Table 35: Forecast carrier revenues for public safety priority data, 2012-2019
Table 36: Key success criteria for mobile IPTV/VoD priority data biz models
Table 37: Forecast users & revs for mobile IPTV/VoD priority data, 2012-2019
Table 38: Key success criteria for M2M/IoT priority data biz models
Table 39: Forecast users & revs for mobile M2M/IoT priority data, 2012-2019
Table 40: Key success criteria for web/app-acceleration data biz models
Table 41: Forecast users & revs for mobile web acceleration priority, 2012-2019 P
Table 42: Forecast unilateral app/VoIP blocking/degrading by MNOs, 2012-2019
Table 43: Key success criteria for "unenforced terms & conditions "models
Table 44: Key success criteria for VoIP & app blocking/throttling biz models
Table 45: Key success criteria for parental content-control biz models
Table 46: Key success criteria for deliberate app-degradation models
Table 47: Key success criteria for user-defined throttling/policy biz models
Table 48: Key success criteria for vertically-integrated "Kindle" biz models
Table 49: Forecast users & revenues for Kindle-model mobile data, 2012-2019
Table 50: Key success criteria for QoS-enabled MVNO data biz models
Table 51: Forecast users & revenues for QoS-enabled MVNO data, 2012-2019
Table 52: Mobile data business models summary & global forecast, 2012-2019
Table 53: Key non-neutral business models revenue global forecast, 2012-2019
Table 54: Non-neutral mobile data models - 1 vs. 2-sided segmentation
Zero-rating of some content will also encourage some users to switch provider, or start on the first rung of mobile Internet use. Two-sided business models might yield 2% of overall mobile data revenues.
Another theme is that some types of non-neutrality are less controversial than others. Some applications are really just about mobile broadband rather than access to the Public Internet.
Mobile operators and regulators should focus first on the former - enterprise connections, leading-edge M2M & IoT uses of cellular, public safety data applications and maybe paid data for mobile advertising. Conversely, so-called "fast lanes" for mobile video or applications are complex to achieve, cause huge controversy and - in the final analysis - likely won't be worth much anyway.
Lobbyists, politicians, telco execs and regulators need to "pick their battles" better.