10 more methods to monetise mobile data

How to measure, compare and improve efficiency within telecoms

Per-Mbyte pricing 10 more methods to monetise mobile data

Prepared for Comptelwww.comptel.com 13 June 2014

tefficientwww.tefficient.com

13 June 2014 1© tefficient and Comptel Corporation 2014

+

http://www.comptel.com/

http://www.tefficient.com/

Still, for some, the Mbyte concept is

difficult

Creating an issue to relate to the

consumption of Mbytes

Uncertainty hampers mobile data adoption

Enrich & complement per-Mbyte model

13 June 2014 2

This presentation is based on the full analysis “10 more methods to monetise mobile data” which contains more details

Per minutePer SMS

Per Mbyte

Data usage up 60-100% per yearVoice & messaging flat at best

It works!

Ten more methods to monetise mobile data1.2.3.4.5.6.7.8.9.10.

Single-user shared dataMulti-user shared dataApps for flat feeApp for freeBundled contentFree tablet dataApp time-based chargingSponsored dataAd-funded mobileVoice over LTE

© tefficient and Comptel Corporation 2014

Method 1

Single-user shared data

• Extra data-SIM(s) under the same allowance

• Sold on the flexibility of being able to use the allowance on several devices• Doesn’t add any data volume

13 June 2014 3

Typical example: Telenor Norway – 49 NOK or 6 EUR

per month

Free example: TDC Denmark – 3 extra data-SIMs free per

phone

0

50

100

150

200

250

300

350

400

Q3 11 Q4 11 Q1 12 Q2 12 Q3 12 Q4 12 Q1 13 Q2 13 Q3 13 Q4 13 Q1 14

Data

-only

SIM

s [t

housa

nds]

Total Business

Intr

oduc

tion

of fre

e da

ta-S

IMs

Method 1: Single-user shared data

Implementation complexity Low

Difficulty for competitors to copy

Low

Differentiation potential Low

Near-constant growth in business data-only SIMs – free of charge intro didn’t

affect this growth


Method 2: Multi-user shared data

Implementation complexity High


High

Differentiation potential Medium

Method 2

Multi-user shared data

• Other users’ SIMs under the same data allowance

• Sold on the flexibility of being able to use the allowance on several devices and users• Doesn’t add any data volume

13 June 2014 4

Example: Verizon’s original offer – 40 USD per added smartphone user,

10 USD per added tablet

2,2

2,3

2,4

2,5

2,6

2,7

2,8

2,9

0

10

20

30

40

50

60

70

80

90

100

Q1 11Q2 11Q3 11Q4 11Q1 12Q2 12Q3 12Q4 12Q1 13Q2 13Q3 13Q4 13Q1 14

SIM

s per

acc

ount

Reta

il p

ost

paid

SIM

s/acc

ounts

[m

illions]

Retail postpaid accounts Retail postpaid SIMs Retail postpaid SIMs per account

Intr

oduc

tion

of m

ulti-

user

sha

red

data Intro of multi-user share

data led to a higher number of SIMs per

account


0

5

10

15

20

25

30

35

40

45

Jun 11 Sep 11 Dec 11 Mar 12 Jun 12 Sep 12 Dec 12 Mar 13 Jun 13 Sep 13 Dec 13 Mar 14

SIM

s/m

em

bers

[m

illions]

au SIMs au SIMs in Personal services segment Smart Pass members

Intr

oduc

tion

of S

mar

tPa

ssMethod 3: Apps for flat fee

Implementation complexity Medium


Medium


Method 3

Apps for flat fee

• A set of apps (e.g. 500 apps within Google Play) for a flat fee per month• Covering download &

use• Makes app-driven

revenue more predictable

• Can increase customer loyalty

13 June 2014 5

30% of au customers in KDDI’s Personal services

segment were Smart Pass members by March 2014 –

two years after launch

Example: KDDI – au Smart Pass 273 JPY [2,6 EUR] per month

Example: Kyivstar – App Club – pay per day


Method 4: App for free



Medium


Method 4

App for free

• Free use of one app• Increase take-up and customer loyalty in distinct segments

13 June 2014 6

Example: GoSmart Mobile, a T-Mobile US sub-brand – zero-rated Facebook

Example: WhatsApp SIM from E-plus – zero-rated WhatsApp

Certain end-users have developed a preference for a specific app

which is stronger than their operator preference

Won’t everyone just copy?Likely not: Requires commercial agreements which often are market exclusiveApp usage should still be monitored – by understanding it, operators can adjust free app offers and through analytics predict the impact of new offers


Method 5: Bundled content



Medium


Method 5

Bundled content

• 3rd party content included into premium service bundles• Motivate a price premium on 4G LTE• Drive data consumption• Steer customers towards a larger bundle• Leverage loyalty to the content brand

13 June 2014 7

Exam

ple

s

Example: Tele2 Sweden – uses HBO to drive customers to at least take the 2 GB tablet plan

Example: Telia Sweden – uses Spotify

for loyalty

Example: Vodafone UK – 4G customers can

choose between Sky Sports, Spotify Premium and (from July) Netflix


Method 6: Free tablet data

Implementation complexity Low


Low


Method 6

Free tablet data

• Tablets: a growth opportunity for operators• USA: 68% of contract net adds Q1 2014 were tablets

• Many under shared data plans (Method 1 & 2)

• Revenue per tablet much lower than from a smartphone customer

• But price premium for a cellular-enabled tablet ~100 EUR

13 June 2014 8

Example: Telenor Denmark – 200 Mbytes of free data per month


Example: T-Mobile USA – 200 Mbytes of free data per month

Q3 2013 (before launch): 5000 net addsQ4 2013 (after launch): 69000 net adds

Subsidisation to Wi-Fi-only price leads to a low business marginCan free tablet data overcome the revenue vs. subsidy dilemma?

For users who otherwise would have stayed Wi-Fi-only rest of month

Method 7: App time-based charging



High

Differentiation potential High

Method 7

App time-based charging

• App access for a limited time• Maturing, prepaid

dominated, markets• To satisfy users’ cash flow

• Mature, bundle dominated, markets where users regularly face a “rest of month” decision• When they exhaust

monthly allowance

13 June 2014 9

“Uninor has decided to shift from volume based Internet offerings (MB and GB

offerings) to service based Internet offerings (Facebook and Whatsapp)”

Example: Uninor India – time-based charging of Facebook and WhatsApp

Use

case

s


• Revenue opportunity for operators• But unlikely to bring any

differentiation potential in the eyes of the end-users

Advertisers know that moving images, especially on personal devices as

mobiles, have the largest impact on us – but if users worry about their data

allowance, they won’t watch

Method 8: Sponsored data



High


Method 8

Sponsored data

• Advertisers and content providers pay operators to zero-rate1 ads or content• Also for end-users without a

data plan – and for end-users who spent their allowance

13 June 2014 10

Example: AT&T – Sponsored data (launched January 2014)Logo indicates that

the content is zero-rated


1) Without any fee and without deducting related Mbytes from an end-user’s allowance

Method 9: Ad-funded mobile



Medium

Differentiation potential High

Wifog’s implementation• Watch 45 seconds of

targeted video ads to get an additional 100 Mbytes of data• Also 120 minutes of voice and

200 SMSs per month

• MVNO on 3’s network• 3G-only access

• 120 000 users after 5 months

Method 9

Ad-funded mobile

13 June 2014 11

Example: Wifog – Ad-funded mobile MVNO in Sweden

End-user proposition:• Accept to view targeted ads• In return, get free mobile use

• Operators could perhaps not set up ad-funded mobile ventures: risk of cannibalising core business

• But hosting ad-funded MVNOs might be good to ensure indirect revenue from “free riders”

Analytics critical for the ad-funded business model as an operator or MVNO needs to show

that the ad targeting works better than in alternative ad channels


Method 10: Voice over LTE

Implementation complexity High


Medium


Method 10

Voice over LTE

13 June 2014 12

With Voice over LTE, operators can offer IP based voice with a substantial quality benefit to over-the-top VoIP

when mobile is used as a channel

• End-users are used to the convenience of having all communication tools in one place• Voice, chat, video, screen sharing

etc• Through OTT services as Lync &

Skype

• But it makes users less mobile since high quality voice-over-IP is rare when on mobile• Voice over LTE can change thisKorean operators SK Telecom, LG Uplus and

KT all launched Voice over LTE 2012. The rest of the world is about to follow – and the development is fast:• docomo, AT&T and ’3’ Hong Kong have

during May said they will launch May-June• GSMA expects 20 VoLTE launches in 2014

Short-term revenue increase isn’t the main target for

operators

Instead it is the positive effect on customer

loyalty and competitiveness which

operators seekTo safeguard long-term revenue

60% of mobile service revenue

in mature markets is voice


Consider all these methods – implement a

fewwhich suit your specific

market and your position in it

Conclusion

13 June 2014 13

*) The presentation is based on the full analysis “10 more methods to monetise mobile data” which contains more details

• End-users buy Mbytes

• Still, for some, the concept of a Mbyte is difficult and hampers mobile data adoption• This presentation outlines* 10 more

methods to monetise mobile data• They all have merit – one winner isn’t

nominated


• Policy and charging capabilities to be integrated natively in the implementations• Charging rules can’t be isolated from policy rules

• Analytics – predictive and based on machine learning – is a critical component for the uptake of these services• And for an operator’s ability to monitor usage and identify new service

alterations

Policy, charging & analytics pointsto consider when implementing the 10 methods


1. Single-user shared data

Policy & charging to support multiple devices per subscriber

Contextual analytics to identify customers with multiple devices and

explore upsell or loyalty potential

2. Multi-user shared data

Policy & charging to support multiple devices per sub and multiple subs per account

QoS policy should be per user and per device, not per account

Contextual analytics to identify users (family, friends, company) who could join an

account and explore upsell or loyalty potential

3. Apps for flat fee, 4. for free

Policy & charging to allow apps to be categorised based on if they fall

under a certain flat rate or not

Contextual real-time analytics to understand usage and predict the

success of new app bundles by finding patterns in big data

6. Free tablet data on top of “1”

Policy & charging to support manual & automatic top-ups

of various sizes & prices

Contextual analytics to personalise top-up

propositions in real-time

5. Bundled content

Policy & charging to adapt to different agreements with different content providers

Predict and promote top-ups while using bundled content

QoS with bundled content1

7. App time-based charging

Policy & charging to monitor time usage per app

Contextual analytics as basis for balancing app-based upsell vs. top-up promotions in real-

time

8. Sponsored data

Policy & charging to allow content to be categorised based on if it falls under a certain sponsored category

or not

Contextual analytics to give advertisers user & usage insight

9. Ad-funded mobile

Policy & charging to track usage of individual users and dynamically provision caps

Contextual real-time analytics to target ads

10. Voice over LTE

Policy control with PCRF to differentiate to OTT VoIP

Policy & charging to allow packing of multimedia in

attractive unified bundles – and contextual real-time

analytics to improve hit rate

1) If compliant with net neutrality legislation

How to measure, compare and improve efficiency within telecoms

Per-Mbyte pricing 10 more methods to monetise mobile data


DOWNLOAD THE FULL REPORT

http://comptelblog.com/2014/06/monetise-mobile-data/