mo
obiqu
uity®
® Mo
oneyy
Interesst Calculaation
n
Feaaturee
Executtive summ
mary
1
Executive summary
Catalyst
The monetization of data services is a high priority for operators at present, especially those rolling out
new infrastructure, who are looking for a rapid return on their infrastructure investment. In order to
fully exploit the capabilities of all-IP networks, operators require solutions that will enable them to
design, develop, deploy, and retire offers rapidly. However these offers must be contextual if operators
aim to: acquire the largest segment of their addressable market; grow customer usage and value, and
retain customers in today’s fast-paced digital world. The newest iteration of smart policy control
solutions, or Policy 2.0, can address these needs and deliver the sought after value from operators’
customer data assets to promote plan-based marketing offers.
Ovum view
Operators can be both enablers and beneficiaries of the rapidly advancing digital life of their
customers. While operators need to invest in their infrastructure and service offers to meet customer
demand, they have to be certain of rapid revenue recognition to recover the sunk infrastructure
investment costs, but equally ensure their marketing operations are able to leverage multiple aspects
of customer data to drive revenue and earnings growth. Using ‘smart policy control solutions’ in
concert with their data repositories must be at the core of an operator’s digital transformation and
data monetization strategies to ensure effective revenue and customer management.
Key messages
ƒ Using smart policy control solutions in concert with their data repositories and customer data
insights must be at the core of operators’ digital transformation and broadband monetization
strategies.
ƒ Operators need to deploy ‘smart policy control solutions’ that integrate PCRF and PCEF solutions
and data from a variety of sources and dimensions. Together they will provide operators with
powerful revenue and customer management tools.
ƒ Contextual policy control solutions can be used effectively in operators’ marketing functions to
deliver marketing use cases for the acquisition, growth, and retention phases of the customer
lifecycle.
ƒ In contrast to previous technically driven policy solutions, the CMO should lead the contextual policy
discussions from a business perspective, and work closely with the CTIO organizations.
ƒ Vendors with integrated offers and a value-added service wrap are solid partners in the ecosystem
of enhanced marketing offers.
2
The digital dilemma
a for op
peratorrs
Consume
er demand fo
or high spee
ed mobile broadband acccess and services contin
nues to grow
w and
operatorss are investin
ng in 4G licenses in developed marke
et and 3G lice
enses in eme
erging marke
ets to
address that
t
demand.. However oth
her players have establish
hed themselvves to capitalize on that grrowth,
but witho
out the expen
nse of buildin
ng our new physical
p
netw
works. Disrup
ptive players such as Am
mazon,
Facebookk and Google have create
ed new value chains and business mo
odels and cha
anged custom
mers’
expectatio
ons in terms of delivery and choice of products, co
ontent and tariff plans; the
ey have also driven
d
customerr expectation for a rapid service
s
delive
ery and online
e accessibilityy and flexibilitty. Figure 1 shows
s
a typical eco-system experienced in many developed marrkets by middle income users.
u
Brickss and
mortar brands have been
b
super ceded
c
by their high growth
h online subssidiaries, or in
n some case
es the
brand and
d business on
nly exist online.
Figure 1: The consum
mer’s digital liifestyle
Source Ovu
um
Operatorss can be bo
oth enablers and beneficiaries of thiss digital life. They need to
t invest in digital
d
platformss and service
es to meet th
hat demand, but critically they need to
o maximize th
he return on their
infrastruccture investm
ment, and generate susta
ainable reven
nue. Using sm
mart policy co
ontrol solutio
ons in
concert with
w custome
er analytics solutions
s
sho
ould be at th
he core of op
perators’ dig
gital life markketing
strategiess. Predictive
e insights and automatted policy solutions tied
d to revenue and custtomer
managem
ment systems allows operators to develop
d
plan-based markketing use cases
c
to add
dress
demands of multiple segments.
s
Big
g data and an
nalytics are the enablers for
f many of the
t plan-based use
cases, bu
ut policy conttrol solutions are the foun
ndation of the
ese offers, as it is here that
t
operatorrs set
the param
meters and triggers for directing an
nd treating in
nsights received from an
nalytics toolss (see
Figure 2)..
3
Figure 2: Components for next generation of policy solutions
Source Comviva
Policy control solutions to leverage customer data
Since its inception, policy control has come a long way. Originally, operators saw it as a network
defense mechanism for use against high data users. Subsequently, it became a blunt instrument for
capping bandwidth before developing to a more sophisticated form of traffic management. Most
recently, with the development of the Sy interface and its proprietary equivalents, integration with online charging systems (OCS) means that policy control will become key to monetizing data services
across fixed and mobile networks as well as opening the way for OTT players to offer services over
existing networks (see Figure 3).
Figure 3: 3GPP PCC architecture
Source: 3GPP
4
The future telco BSS infrastructure will consist of a horizontal architecture of highly integrated
modules, built around a rules-based engine that can manage and operate services in real time across
fixed and mobile networks. That prospect is getting ever closer and the integration of policy control and
online charging is a first step toward achieving that goal. When implemented separately, the PCRF
(Policy Control and Rules Function) controls bandwidth resources and the OCS platform deals with
charging. Although this arrangement is adequate to support basic tiered pricing, data caps, and fair
usage, it does not offer the flexibility and sophistication of fully integrated components. The logic behind
integrating the PCRF and OCS, commonly referred to collectively as Policy Control and Charging (PCC),
is that a direct interface between the two should make it possible to use charging rules and other data
derived from the BSS layer and elsewhere to manipulate network resources and support more
complex, customer-facing offerings. However, in reality the interface between policy and charging
remains proprietary. The downside is a lack of flexibility in rapid plan introduction, unnecessary vendor
lock-in, and higher cost of operations for mobile operators. Mobile operators need to move away from
proprietary policy implementations and adopt open a standards-based solutions to exploit data
monetization opportunities.
The next generation of policy solution needs to be a flexible tool and offer more personalized Quality of
Experience (QoE), granular pricing plans based on multiple factors (application, usage, bearer,
preferences, location, and time of day), as well as the ability to launch new services and plans more
quickly, and better understand consumer habits using real-time analytics. To fully exploit this
functionality, it is vital that the revenue management solution should be context-aware. This is achieved
with the integration of PCC and analytics using data derived from a number of sources – a Policy 2.0 if
you will, as shown in Figure 4.shows some of the sources from which data can be derived and how it
can be used in Policy 2.0.
Figure 4: Policy underpins data monetization
Data
monetizati
on
Marekting
use cases
Caching &
optimizati
on
Customer
managem
ent
Business
process
analytics
Converged
billing
Rating and
charging
Policy
managem
ent
Traffic
shaping
Source Ovum, Comviva
5
ging data at a customer, service and network
n
levels, policy soluttions can sup
pport the follo
owing
By leverag
marketing
g and care ce
entric use cases for:
ƒ Acquirring new custtomers
ng existing cu
ustomers and
d their usage
e, and managing the custo
omer lifecycle
e
ƒ Growin
ƒ Retain
ning customers and avoiding churn.
Figure 5 shows
s
the va
arious stagess operators go through to perfect theirr policy-drive data monetizzation
with marrketing opera
ations in min
nd. As shown, these sta
ages overlap the phases in the custtomer
lifecycle; the
t use casess we identify for a specificc area below, can just as easily
e
be offered in other areas
a
depending
g on the operrator’s intern
nal definitionss.
Figure 5:
5 Policy-driven
n marketing offers
o
acrosss the customer lifecycle
Source Com
mviva, Ovum
Conte
extual policy
p
s
solution
ns for market
m
ing ope
erationss
Acquirring custo
omers ussing conte
extual policy
Applicattion- or conttent-based plans
p
Applicatio
on plans drivve higher da
ata usage byy extending plans tailore
ed to the cu
ustomers’ co
ontent
preferencces – examp
ple, gaming, sports,
s
social networking, YouTube orr Netflix. In emerging
e
and
d lowincome markets,
m
the high charge associated with
w data serrvices deters mass-adoptiion, so a web
b-only
plan is an
nother way to
o apply policy to offer a ba
asic, text-only version of se
ervices to use
ers. On accou
unt of
the low bandwidth
b
inttensity of the
ese services, the plans are
a priced afffordably, significantly low
wering
barriers to
t entry for lo
ow-income se
egments.
6
Shared device plans
Device-plans enable definition of service permissions based on the handset type and ensure that the
4G or 3G phones for example phones receive higher bandwidth entitlements compared to simple
feature phones. Device plans can also be developed for the Internet of Things ecosystem, where many
‘dumb’ terminals and sensors are also attaching to the IP network.
Equally device-based plans enable definition of service entitlements based on the handset type. For
example, customers with smart devices may receive higher bandwidth entitlements in comparison to
customers who use an intermediate range of devices. The same concept can be applied to the Internet
of Things – one of the most innovative applications is the car. For example, AT&T has been very
aggressive and successful with its AT&T Connected Car program over the past few years (see Figure
6). AT&T has agreements with many of the major car manufacturers (OEMs) but also has been
developing programs with after-market providers. AT&T’s program has not only grown their mobile
subscriber base but it has also enabled AT&T to create some very unique mobile offers to the entire
connected car ecosystem including its mobile customers. With this coverage and its use of policy
solutions, AT&T can add a subscriber’s connected car to family share plans (Mobile Share Value Plan),
negating the need for additional contracts. The initial proposition connected a General Motors car
using LTE, for $10 per month, the same cost as a tablet.
Figure 6: AT&T Shared device plan
Source AT&T
7
Growing customers value using contextual policy solutions
Shared data plans
With the average number of mobile devices per person expected to reach four per user by 2020,
shared data plans can be a method for operators to exploit that trend and increase the chances of
retaining customers. A shared data plan allows users to divide a pool of data either between devices or
within a family or group. The account holder can define access permissions and allocate volume, time
and monetary limits as well as specify services that can be used by each device or user, and make
adjustments to individual allocations as required after the initial set up. Customers only receive one bill
for all devices and proactive mobile alerts to help them to stay on top of their data usage. If there is
data remaining in the plan at the end of the period, then policies can be set to allow certain
subscriptions to roll that over to the next month/charging period. For the operator, it increases the
revenue per plan by getting the customer to buy more data, and it also locks in the customer and
raises the barriers for churn
Personalized tariffs
Customers can build their own service plan or bundle from a menu of options and choices. There will
be predefined bundles of voice, texts, data, and then customers can add the content or applications
they want to fit their price point and device. By allowing customers to pay just for the services they use
and want, operators are far more likely to keep their customer. If the customer is forced to buy a large
expensive bundle just to gain access to the one or two things they will leave at the earliest opportunity.
Real-time marketing campaigns
Operators can leverage insights into network conditions and user transaction patterns to deliver
targeted offers in real-time to customers. Based on a set of predefined customer transactional
triggers, marketing functions can configure a range of promotional products and can automatically
action the most optimal offer over the customer’s preferred interaction channel.
Control and management
The judicious use of policy, OCS and analytics also helps operators define bespoke packages. Eligible
customer can be given access to offers, and enterprises too can use it to manage their business. For
example, enterprise receive group plans or buckets of calls, text messages and a pre-set volume of
data which the enterprise customer can then allocate to different areas of the business as required
(see Figure 7).
8
Figure 7: Enabling enterprise customers to control usage
Source: Ovum
Drive adoption of new technologies
Policy solutions, in conjunction with analytics to help drive take up of new services such 3G in emerging
markets and 4G and VoLTE in developed markets, and so ensure that operators have a faster return
on investment. So for example, if a 3G user is a heavy data user and repeatedly uses a certain amount
per month, the policy can be set to identify them as part of the segment to target with a 4G upgrade.
Once upgraded to 4G, the operator will then look at promoting services such as home automation. To
drive users from 2G to 3G, operators will use innovative pricing plans to stimulate usage.
In one example, an operator in South East Asia used policy and analytics to track inbound roamers,
monitor their network usage then sent users with 4G-enabled devices an SMS broadcast to make
them aware that they could access the LTE services, and the costs to do so - and also alert them of
4G-related promotions. The operator offered tailored promotions based on the nationality and type of
customer (business or pleasure). During the soccer World Cup, OiBrazil launched ‘Oi Tourist WiFi’,
which allowed foreign users to access the operator’s WiFi network for free whilst in Brazil. The service
was accessed via an app, however they had to connected to Oi Brazil’s mobile network in international
roaming also. Again policies could be set to ensure only the permitted users were able to access this
service.
Retaining customers using contextual policy solutions
Customer lifecycle management
Being able to utilize data from many sources and offer contextualized services will be vital to
monetizing data services, however the use of policy also means that the customer lifecycle itself can be
9
micro-managed, increasing ARPU and reducing the risk of churn at the same time. Figure8 shows how
policy and analytics can be used to automatically manage the customer with a set of pre-determined
rules which offer inducements and apparent discounts at critical points in the lifecycle.
Figure 8: Managing the customer lifecycle using policy and analytics
Source: Ovum
Top-ups
Typically, the customer lifecycle starts with a pay-as-you-go package which offers free access to social
media and, once the customer has become familiar with using data that is followed by an offer to
purchase 1GB of data valid for one month and with an extra 200MB free as an inducement.
If the customer uses the data allowance a few days before the end of the one month validity period, two
possible scenarios are offered. The customer is offered the chance to either purchase another 1GB of
data at a 20% discount with usage starting immediately, or alternatively, they can buy the 1GB
package at full price but extend the validity period to cover the remaining period until the next monthly
usage cycle. With the customer now firmly in the habit of using mobile data services on a regular
basis, the offers are oriented more towards speed of access, with subsequent upsells aimed at
increasing bandwidth, extending validity periods and locking in other users with the opportunity to
share unused bandwidth.
One Chinese mobile operator uses policy and analytics to ensure that prepaid customers nearing the
end of their credit will be targeted with specific offers or promotions. The operator also analyzes the
customer's usage data in real-time to monitor when and how they are likely to add more credit; it uses
a combination of policy, BSS data and analytics to retain customers.
10
Self-care
While care is a separate function to marketing, there is a close link between the two and advances in
personalized and contextual marketing and outreach has to be matched by personalized and
contextual care. This can range from bill shock management, to contextual IVRs and mobile apps that
provide instant views of account status (including shared plans and devices), outstanding offers, and
the ability to upgrade packages and change selected parameters without having to contact the
operators.
Support QoE and QoS requirements
Operators can exploit real-time data on cell traffic and customer activity data to deliver an improved
Quality of Experience (QoE). Plans based on QoE allow operators to prioritize bandwidth for select
customers even in peak hours and locations, assuring them a consistent service experience. PCRF
also allows operators to manage network capacity and performance in relation to customer usage,
while PCEF will manage bandwidth or the radio access network, and adapt and enforce policies to
manage the traffic throughput. Both of these policy solutions are key to managing multiplayer gaming
and live streaming services.
Addressing new segments
Machine to machine (M2M) or IoT services
Apart from enabling the provisioning of new services, the integration of PCRF (policy and charging rules
function) and OCS (online charging system) is also promising to breathe new life into what for many
years has been a nascent market: machine-to-machine (M2M) communications. The main difficulties
with M2M from a mobile operator’s point of view have always been that it is a low-ARPU service and
one that in many instances requires a disproportionate amount of bandwidth. The rollout of higherspeed mobile data technologies, such as HSPA and LTE, will enable operators to handle the expected
growth in the number of M2M terminals in terms of capacity, but the available bandwidth might not be
enough on its own to enable operators to meet their QoS commitments in support of M2M and at the
same time serve their other customers.
The business case for offering M2M services therefore rests on the operator’s ability to maximize the
number of chargeable events or traffic flow while minimizing the impact on the rest of the network. In
addition, infrastructure costs have to be kept to a minimum if profitability is to be maximized. In this
respect, operators that have already installed policy control as a means of managing mobile data
traffic have an advantage. Although they will be able to support basic M2M services, implementing
integrated PCRF/OCS means that the real-time interaction between PCRF and OCS can be exploited
to meet the challenges posed by M2M and in addition enable a range of value-added services.
11
Vend
dors pollicy solu
utions for the
e operattors sh
hort listt
BSS ve
endors well placed
d for Policcy 1.0
Competitiion among PCC
P
software vendors has
h intensified in last thrree years, with
w
major players
competing internation
nally for broa
ader market penetration and more widespread
w
ad
doption withiin the
telecoms vertical. Reccognition thatt fully integratted policy con
ntrol and onliine charging systems wou
uld be
at the corre of IT infrasstructure. Ma
ajor BSS vendors acquire
ed companiess or invested internally to get a
marketab
ble, integrated policy conttrol and OLC
C solution. Typical examples are Amdo
ocs’ acquisitiion of
Bridgewater, Oracle’ss purchase of
o Tekelec, an
nd CSG’s pu
urchase of ce
ertain assetss of billing ve
endor
Volubill. In
n all these cases, the larrger vendorss were able to
t replace th
heir internallyy developed policy
control an
nd rules funcction (PCRF) with the acq
quired techno
ology, howeve
er they, and all vendors in this
space nee
ed to be mind
dful of the req
quirement off Policy 2.0, where
w
simple and clean inttegration bettween
policy con
ntrol, chargin
ng and analyttics will delive
er IT and bussiness agility and a more customer ce
entric
operation
n (see Figure 9).
Figure 9:
9 The evolutio
on of policy so
olution
Source Ovu
um, Comviva
Vendorrs to support Policy 2.0
The use of
o policy for basic
b
traffic managementt and quota management, usually refferred to as Policy
1.0, has evolved
e
into customer-faci
c
ing Policy 2.0
0, which when
n integrated with
w OCS can
n offer a vast array
of service
e and bundling
g options whe
en allied with a wide range
e of historical and real tim
me data.
Ultimatelyy, the goal is to offer upsselling, cross--selling, disco
ounting, and other marketing campaig
gns in
real time, and this will see furthe
er companiess competing in this spacce, such as integrated se
ervice
and/or in
ndependent companies
c
likke Comviva. The advantage of an inde
ependent policy vendor iss that
their policcy solutions can be deplo
oyed as need
ded, and ope
erators will have the flexib
bility to selecct the
right type
e of solution rather than be
eing locked in
n to integrate
ed policy offerrs from large
er vendors su
uch as
Ericsson and
a Huawei.
12
Appendix
Methodology
This paper was researched, authored and produced by Ovum in association with Mahindra Comviva, as part of
a series of papers assessing the current state and future market direction of data monetization services for
mobile operators.
About Mahindra Comviva
Mahindra Comviva is the global leader in providing mobility solutions. It is a subsidiary of TechMahindra and a
part of the USD16.7 billion Mahindra Group. With an extensive portfolio spanning mobile finance, content,
infotainment, messaging and mobile data solutions, Mahindra Comviva enables service providers to enhance
customer experience, rationalize costs and accelerate revenue growth. Its mobility solutions are deployed by
130 mobile service providers and financial institutions in 90 plus countries, transforming the lives of over a
billion people across the world. For more information, please visit www.mahindracomviva.com.
Author
Clare McCarthy, Practice Leader, Telecoms Operations and IT: [email protected]
Ovum Consulting
We hope that this analysis will help you make informed and imaginative business decisions. If you have further
requirements, Ovum’s consulting team may be able to help you. For more information about Ovum’s consulting
capabilities, please contact us directly at [email protected].
Copyright notice and disclaimer
The contents of this product are protected by international copyright laws, database rights and other
intellectual property rights. The owner of these rights is Informa Telecoms and Media Limited, our affiliates or
other third party licensors. All product and company names and logos contained within or appearing on this
product are the trademarks, service marks or trading names of their respective owners, including Informa
Telecoms and Media Limited. This product may not be copied, reproduced, distributed or transmitted in any
form or by any means without the prior permission of Informa Telecoms and Media Limited.
Whilst reasonable efforts have been made to ensure that the information and content of this product was
correct as at the date of first publication, neither Informa Telecoms and Media Limited nor any person
engaged or employed by Informa Telecoms and Media Limited accepts any liability for any errors, omissions or
other inaccuracies. Readers should independently verify any facts and figures as no liability can be accepted in
this regard - readers assume full responsibility and risk accordingly for their use of such information and
content.
Any views and/or opinions expressed in this product by individual authors or contributors are their personal
views and/or opinions and do not necessarily reflect the views and/or opinions of Informa Telecoms and
Media Limited.
Disclaimer
All Rights Reserved.
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form by any means,
electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of the publisher, Ovum (an Informa
business).
The facts of this report are believed to be correct at the time of publication but cannot be guaranteed. Please note that the
findings, conclusions, and recommendations that Ovum delivers will be based on information gathered in good faith from both
primary and secondary sources, whose accuracy we are not always in a position to guarantee. As such Ovum can accept no
liability whatever for actions taken based on any information that may subsequently prove to be incorrect.
13