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Mobile Broadband Business Models:
Sponsored Data & Zero-Rate Charging
Dean Bubley, Disruptive Analysis
London, 30th June 2014
dean.bubley@disruptive-analysis.com @disruptivedean
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 2014 June 2014
Telecoms industry in a nutshell
Copyright Disruptive Analysis Ltd 2014 June 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
The big problem for the mobile industry…
Copyright Disruptive Analysis Ltd 2014 June 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 spend Source: Disruptive Analysis “Non-Neutral Mobile Broadband” report, June 2014
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
Zero launches
Samsung
Galaxy
range
starts
Android
goes
mainstream
Kindle 3G
Whispernet T-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 2014 June 2014
Open Internet access was not original intent for 3G data services
Mobile data: Tsunami or just normal rising tide?
Copyright Disruptive Analysis Ltd 2014 June 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
Many issues for app-based biz models
Copyright Disruptive Analysis Ltd 2014 June 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
Two different worlds for mobile data-plans
Copyright Disruptive Analysis Ltd 2014 June 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
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 2014 June 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”
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 2014 June 2014
Zero-rated data – attractiveness matrix
Copyright Disruptive Analysis Ltd 2014 June 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:
Zero-rating examples are already widespread
Copyright Disruptive Analysis Ltd 2014 June 2014
Use of zero-rating will continue to grow strongly
Copyright Disruptive Analysis Ltd 2014 June 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
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 technology Paid 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 2014 June 2014
Sponsored data – attractiveness matrix
Copyright Disruptive Analysis Ltd 2014 June 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
Sponsored data…. so far, mostly just AT&T
Copyright Disruptive Analysis Ltd 2014 June 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
Sponsored data – limited growth potential
Copyright Disruptive Analysis Ltd 2014 June 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
Successful non-neutral models
Legally permissible
Technic –ally
feasible
Consumer demand
App / content player appeal
Copyright Disruptive Analysis Ltd 2014 June 2014
Practical forms of non-neutral
mobile broadband only a
small % of the conceptual
variants & use-cases
Policy & innovation…… …..vs. politics
Copyright Disruptive Analysis Ltd 2014 June 2014
Strategy
Mobile broadband
control
In-house apps & content
Marketing / Product
IT Core network
Radio network
Devices
Legal
Tensions
Tensions
Distance
Net/Not neutrality won’t stop data flattening too
Copyright Disruptive Analysis Ltd 2014 June 2014
Sponsored data, paid-priority QoS etc will have negligible financial impact
Source: Disruptive Analysis Non-Neutral MBB Report
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 2014 June 2014
Copyright Disruptive Analysis Ltd 2014 June 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
www.disruptive-analysis.com
disruptivewireless.blogspot.com
@disruptivedean
information@disruptive-analysis.com
Skype:disruptiveanalysis
Copyright Disruptive Analysis Ltd 2014 June 2014
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