Sponsored data and zero rate charging - Non-neutral mobile broadband models

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Analysis & forecasts for two key types of application-based charging / non-neutral mobile Internet business models.

Zero-rating of mobile data is used to exempt certain applications or content from users' data plan quotas, and is used in both developing and mature markets. In essence, nobody pays for the data - although the mobile operator may work a revenue-share deal for paid content, or may look to upsell the users with more paid data access.

Sponsored data is similar, but involves the content/app provider paying for data traffic on behalf of the user. It has been popularised by AT&T's announcement in January 2014, although it has gained only limited traction so far.

This presentation, based on Disruptive Analysis' June 2014 on Non-Neutral Mobile Broadband models, examines the sub-segments and likely success factors for each type of offer.

Published in: Internet, Technology, Business

Sponsored data and zero rate charging - Non-neutral mobile broadband models

  1. 1. Mobile Broadband Business Models: Sponsored Data & Zero-Rate Charging Dean Bubley, Disruptive Analysis London, 30th June 2014 dean.bubley@disruptive-analysis.com @disruptivedean
  2. 2. About Disruptive Analysis  London-based tech analyst house & strategic consulting firm  Cross-silo, contrarian, independent  Advisor to telcos, vendors, regulators & investors  Research reports, internal workshops & advisory projects  Clients include many top telcos, vendors, webcos & startups  Speaking roles at 30+ events per year in Europe, US & Asia  Research on “Telco-OTT Strategies”, WebRTC etc  New Strategy Report on “Non-Neutral Broadband Models” Twitter @disruptivedean Blog: disruptivewireless.blogspot.com Copyright Disruptive Analysis Ltd 2014June 2014
  3. 3. Telecoms industry in a nutshell Copyright Disruptive Analysis Ltd 2014June 2014 Flat/falling telephony Declining SMS Direct/Internet competition Substitutes & alternatives Costly infrastructure Regulatory impact Data still growing Digital content Verticals Telco-OTT APIs & partnerships Better segmentation
  4. 4. The big problem for the mobile industry… Copyright Disruptive Analysis Ltd 2014June 2014 0 200 400 600 800 1000 1200 1400 2012 2013 2014 2015 2016 2017 2018 2019 Voice telephony VAS / digital Internet/data access SMS/MMS $bn – Global Mobile Operator Revenue ? New/partner services? Voice/video-based? Verticals? High-end mobile users already nearing saturation for mobile Internet spendSource: Disruptive Analysis “Non-Neutral Mobile Broadband” report, June 2014
  5. 5. 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Huawei E220 USB modem Original iPhone (browser only) iPhone 3G + AppStore H3G open- Internet access (+Skype etc) NTT DoCoMo iMode, 1999 Nokia 9000 with HTML & modem, 1996 O2/HTC XDA Facebook Zero launches Samsung Galaxy range starts Android goes mainstream Kindle 3G WhispernetT-Mobile Web’n’Walk Verizon BREW app store AT&T sponsored data 1st LTE network & zerorated music iPad 3G KPN threatens OTT charging Tuenti zero- rates TelcoOTT WebRTC app History of mobile data business models/devices Galaxy Note LTE Phablet Copyright Disruptive Analysis Ltd 2014June 2014 Open Internet access was not original intent for 3G data services
  6. 6. Mobile data: Tsunami or just normal rising tide? Copyright Disruptive Analysis Ltd 2014June 2014 3G/4G Smartphone data use • Disruptive Analysis has doubts on realism of some traffic forecasts • Growth manageable with pricing, small cells, LTE, LTE-A. 5G is mostly hype for now • “Spectrum crunch” narrative highly questionable (landgrab vs broadcast?) 0% 20% 40% 60% 80% 100% 120% 2012 2013 2014 2015 2016 2017 2018 2019 Growing usage per smartphone Growing # smartphone subs ? NB 2012-13 subs growth possibly skewed by older smartphones without data plans Smartphone data use growth year-on-year c20-30% growth/user/yr Source: Ericsson, Disruptive Analysis
  7. 7. Many issues for app-based biz models Copyright Disruptive Analysis Ltd 2014June 2014 No clear definition of “app” Business model fit Device depend- ency Device OS API exposure HTML5 WiFi fit OSS / BSS head- aches Pricing, selling, support Network depend- encies Arbitrage & other side- effects Organis- ational troubles Mobile differs vs. fixed Non-neutral models of mobile broadband access face a broad range of generic issues in implementation & commercialisation
  8. 8. Two different worlds for mobile data-plans Copyright Disruptive Analysis Ltd 2014June 2014 Source: Disruptive Analysis “Non-Neutral Mobile Broadband” report, June 2014 Nobody who can afford the whole Internet will be happy with just half of it
  9. 9. Application-based mobile data models Mobile Data models Neutral open access User pays for all data Certain data zero-rated Certain data sponsored Partial Internet access Specific applications allowed Specific applications blocked Differentiated Internet access Paid priority “specialised” services Differentiated Wholesale / MVNO Copyright Disruptive Analysis Ltd 2014June 2014 Many of today’s mobile broadband plans “Fully neutral mobile Internet” Data treated equally, charged differently: “Grey Area” Data treated differently by network “Non-Neutral”
  10. 10. Zero-rated data: 4 sub-types • “Data inclusive” for video, music, gaming etc. sold by telco • Long history of zero-rating eg for MMS, BlackBerry data traffic • Competitive advantage in deal-making, not data subsidy Paid bundled apps / content • Mostly used in developing markets; Facebook/WikiPedia Zero • Risks of market distortion vs. benefits of digital inclusion • Already very widely-used (but now banned in Chile) Free apps / content • Most operators developing own comms/content apps • Available to all Internet users, but poss. free for on-net subs • Helps bridge Digital/OTT efforts with existing bundles Telco-OTT apps • Long history of zero-rating data for OSS/BSS purposes • Self-care, updates, billing portals, customer service helpdesks • Mostly not Internet-based but private internal data network Self-care & self- service Copyright Disruptive Analysis Ltd 2014June 2014
  11. 11. Zero-rated data – attractiveness matrix Copyright Disruptive Analysis Ltd 2014June 2014 Good Fair Poor Bad Source: Disruptive Analysis “Non-Neutral Mobile Broadband” report, June 2014 Attractiveness for mobile operators vs. key criteria Telco- OTT apps Paid apps / content Free apps / content Self- care & service Ease of implementation Ease of selling by telco Ease of buying by client Revenue potential Impact on network Reputational risk Market maturity required Workarounds/"gotchas" Adjacent revenues/costs Prevalence 2014 Prevalence 2019 Sponsored data for:
  12. 12. Zero-rating examples are already widespread Copyright Disruptive Analysis Ltd 2014June 2014
  13. 13. Use of zero-rating will continue to grow strongly Copyright Disruptive Analysis Ltd 2014June 2014 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2012 2013 2014 2015 2016 2017 2018 2019 Global mobile Internet users exploiting zero-rated data, m, year-end, est. Source: Disruptive Analysis “Non-Neutral Mobile Broadband” report, June 2014 Note: excludes non-Internet zero-rating eg of MMS & BlackBerry BIS data
  14. 14. Sponsored data: 4 sub-types • Advertiser pays to send ads/promos/demo etc • Fits into existing ad-buying value chain • Consumers resent paying to “be advertised at” • Concept believed to be invented by Disruptive Analysis in Nov 2010 Paid advertising traffic • Data relating to specific URLs is paid by site owner • Highly unclear there is either demand or robust technologyPaid website traffic • Certain applications’ data traffic is paid-for by app provider • At least 10 separate major problems. Almost unworkable • In extremis, risks replacing retail data fees with cheap wholesale Paid app data (1-800 apps) • Companies pay for employees’ work data used on own devices • Potential to combine with VPN/BYOD & other solutions • Moderate potential but business-case unproven Enterprise/BYOD paid data Copyright Disruptive Analysis Ltd 2014June 2014
  15. 15. Sponsored data – attractiveness matrix Copyright Disruptive Analysis Ltd 2014June 2014 Ads Web Apps BYOD Ease of implementation Ease of selling by telco Ease of buying by client Revenue potential Impact on network Reputational risk Market maturity required Workarounds/"gotchas" Adjacent revenues/costs Prevalence 2014 Prevalence 2019 Sponsored data for: Good Fair Poor Bad Source: Disruptive Analysis “Non-Neutral Mobile Broadband” report, June 2014 Attractiveness for mobile operators vs. key criteria
  16. 16. Sponsored data…. so far, mostly just AT&T Copyright Disruptive Analysis Ltd 2014June 2014 ? Plus one or two other unproven rumours (trials?) Advertising partners Enterprise mobile app partners Very few sponsored-data customers announced or reported by users As well as many technical complexities, sponsored data models need strong partnerships to sell/support
  17. 17. Sponsored data – limited growth potential Copyright Disruptive Analysis Ltd 2014June 2014 Sponsored Mobile Data revenues, worldwide, $bn Source: Disruptive Analysis “Non-Neutral Mobile Broadband” report, June 2014 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 2012 2013 2014 2015 2016 2017 2018 2019 Advertising traffic Other use-cases Sponsored data expected to be <1% total mobile broadband revenue in 2019 Sponsored data may reach 3-5% total mobile advertising budgets
  18. 18. Successful non-neutral models Legally permissible Technic –ally feasible Consumer demand App / content player appeal Copyright Disruptive Analysis Ltd 2014June 2014 Practical forms of non-neutral mobile broadband only a small % of the conceptual variants & use-cases
  19. 19. Policy & innovation…… …..vs. politics Copyright Disruptive Analysis Ltd 2014June 2014 Strategy Mobile broadband control In-house apps & content Marketing / Product ITCore network Radio network Devices Legal Tensions Tensions Distance
  20. 20. Net/Not neutrality won’t stop data flattening too Copyright Disruptive Analysis Ltd 2014June 2014 Sponsored data, paid-priority QoS etc will have negligible financial impact Source: Disruptive Analysis Non-Neutral MBB Report
  21. 21. Conclusions  Mobile operators hope to increase data revenues & control  Developed markets: segmentation, loyalty & bundling add value  Developing markets: converting low-ARPU voice users to data  Pricing differentiation easier & less controversial vs. QoS  Two-sided business models sounds theoretically appealing…  … but are virtually impossible to create for mobile data  Zero-rating already widely used & will grow further  Applicable to free & paid content, plus admin & self-care tools  Some questions over neutrality, but arguments mostly weak  Sponsored data largely unworkable, except for advertising  Generic 1-800 apps model almost impossible to create, sell or manage  Bottom line: Zero-rating is key “mostly neutral” model Copyright Disruptive Analysis Ltd 2014June 2014
  22. 22. Copyright Disruptive Analysis Ltd 2014June 2014 Published June 2014: Non-Neutral Mobile Internet Business Models Report On request: private workshops & expert advisory retainers For details email information@disruptive-analysis.com
  23. 23. www.disruptive-analysis.com disruptivewireless.blogspot.com @disruptivedean information@disruptive-analysis.com Skype:disruptiveanalysis Copyright Disruptive Analysis Ltd 2014June 2014

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