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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

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.

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.

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.

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.

Vendors with integrated offers and a value-added service wrap are solid partners in the ecosystem

of enhanced marketing offers.

2

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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 on-

line 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

Customer managem

ent

Marekting use cases

Business process analytics

Caching & optimizati

on

Converged billing

Policy managem

ent

Rating and charging

Traffic shaping

Source Ovum, Comviva

5

By leverag

marketing

ging data at a

g and care ce

a customer,

entric use ca

service and n

ses for:

network levels, policy soluttions can suppport the folloowing

Acquirring new custtomers

Growinng existing cuustomers andd their usagee, and managing the custoomer lifecyclee

Retainning customers and avoiding churn.

Figure 5 s

with mar

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Figure 5

Source Com

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barriers t

5: Policy-driven

mviva, Ovum

extual p

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policy s

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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 higher-

speed 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

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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: clare.mccarthy@ovum.com

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 consulting@ovum.com.

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.

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