Posted: April 25th, 2013 | Author: Malla Poikela | Filed under: Events, Industry Insights | Tags: charging, data pricing, OTT, policy control, real-time charging, real-time policy | Comments Off on Policy Control and Data Pricing Conference 2013: Policy Decisions, Revenue, and Marketing’s Changing Responsibilities
At the Policy Control and Data Pricing Conference 2013 last week, I attended an interesting panel discussion that spoke about how marketing’s role was evolving when it came to policy and charging decisions. One of the most important takeaways was that marketing is going to have to get more involved in policy control and charging acquisition decisions, which has largely been the territory of telecom and IT departments.
That’s because, these days, CSPs are not seeing policy as an independent function. Instead, the focus is more on generating money with policy and charging tools.
The reason that marketing’s input is getting crucial is that, with revenues from voice and text on the decline, communications service providers (CSPs) have to create strategic, adaptive and sticky policies and charging bundles to monetise data. Cooperation with OTTs is becoming more important, because businesses need to develop flexible, joint offering models that can be adjusted for an increase in the revenue from data and cover the investment costs of ever-growing data networks.
Marketing is interested in developing an environment which makes it easy to offer targeted policy and charging bundles to customers, which is difficult to implement without the help of predictive analytics that can determine individual usage patterns and behaviour.
Combining Policy with Monetisation
Most CSPs today treat policy and charging as separate from strategic monetisation campaigns, but that’s changing. The panel showed that many businesses are thinking about policy and charging as a way to create a holistic approach to providing customers with the most relevant services. As data becomes the dominant force of monetisation, CSPs will have to transform policy control from static to dynamic and from reactive to proactive… and this is where marketing comes in.
Traditionally, policy decisions were predominantly made by telecom and IT departments, but as more emphasis is placed on analytics and ROI, marketing will have to be integrated into the mix. Now it’s time to analyse the information more thoroughly, and look beyond data usage per customer into what kind of data is used, by whom, at what times, and through which context, and make sophisticated predictions about the potential change of data usage or risk of churn. All in all, policy and charging models are going to become more complex, which in turn requires accurate network planning, end-to-end design and implementation capability.
Marketing will have to work with IT and telecom to target policy and charging models at a much more granular level. Each customer will have to be offered a policy and charging based on current and predicted behavior and data usage trends. Analytics tools will be the key to not just determining existing trends, but planning for new ones and responding to them in real-time or near-realtime, depending on each use case’s requirement.
The Paradox: Real-Time Policy and Real-Life Turnaround
As the panel explained, the problem right now is that the creation and management of policy control is not flexible or efficient enough. Often, policy models touch many parts of the organization, so decisions have to get approved by multiple departments and multiple levels of management before going into action. In these cases, CSPs risk losing serious revenue opportunities by not responding to customer needs quickly enough.
So, how can CSPs find efficient tools and simplify the process so that these new, innovative services will reach the audience fast enough?
Real-time analytics require real-time turnaround, but right now there are a lot of requirements for any policy change. It can take up to six months or more to deploy new policies, which inhibits the growth of the flexible environment needed to improve the deployment cycle in the first place.
The panel concluded by saying that there is a need to discover a way to simplify the process involved in policy creation. At Comptel, we’ve worked hard to provide some of those tools, with our analytics-driven mediation, policy control and charging platform. The answer to simplifying policy control and charging may be found in the new tools for CSPs that are available, which can better help marketing, IT, and telecom all come together to build business growth.
Posted: April 19th, 2013 | Author: Malla Poikela | Filed under: Events, Industry Insights | Tags: analytics, charging, LTE, policy control | Comments Off on Policy Control and Data Pricing Conference 2013: Where is Telco Policy Heading?
This week, I attended the Policy Control and Data Pricing Conference in Berlin and came away with a lot of interesting insights. One of the subjects was, of course, the future of policy control and charging (PCC). As mobile devices diversify, so, too, do the ways that people use them. Consequently, communications service providers (CSPs) are going to have to think about PCC in a whole new way.
Policy should now be pervasive across all customer touch-points and platforms. Agility and flexibility is going to be paramount in new use cases, because CSPs are going to see a near-limitless combination of mobile data usage bundles, particularly when it comes to multimedia use. To meet this demand, there will have to be innovative new policy and charging models.
The Troubling Siloes of OCF and PCRF
Right now, most PCC efforts are separated. That can be a huge barrier, since OCF (Online Charging Function) and PCRF (Policy and Charging Rules Function) efforts can be stuck in siloes and CSPs can find it difficult to integrate them. However, now there are a lot of requirements coming from the market for diverse policy use cases that require integrated charging capabilities. On the other hand, policy is becoming more and more a strategic monetisation engine for CSPs. Given that there will be so many different use cases in the coming years, which need to be launched to the market quickly, it’s inevitable that policy control and charging systems are going to grow together, so keeping the two separate will do more harm than good. Policy offerings will grow more complex as use cases grow more diverse. Not only that, “policy” is something that spans all networks – applications, BSS, OSS, every device is affected by policy control.
Still, once there’s a platform that can scale alongside policy and charging solutions, PCC is going to be critical for CSPs. It’s clear that, as policy and charging evolve, so, too, will pricing bundles. CSPs that can create versatile bundles and use predictive analytics to offer them to the right customers at the right time will have a huge advantage in the coming years. Predictive analytics together with catalog-driven policy and charging will form in the future the environment to correspond customer’s ever-growing need for individually targeted packages and make them available fast.
Without the relevant user data, it’s impossible to personalise policies effectively. That’s important, given that presenters at the Policy Control Conference seem to believe that innovative strategies for policy will rely on increasing personalisation. So, it’s time for CSPs to consider how they can leverage the big data already at their disposal for meaningful customer insights so they can better monetise their services.
A prime example here is LTE deployment. During the Mobile World Congress, we heard how LTE service has proven to be difficult to monetise effectively, given that customers often don’t use LTE to its full potential and CSPs have to heavily subsidise LTE handsets. With the help of predictive analytics we should on the one hand target the LTE bundles with the subsidised handsets for the customers who would have the greatest benefit. But on the other hand by creating new policies based on user and usage data, it’s possible to create unique bundles that can make LTE a flexible service that becomes available when customers need it, not before. A good example is the instant bandwidth refreshment – also known as the turbo boost – to satisfy customer’s increased data usage.
This conference has highlighted what we here at Comptel have known for some time: real-time policy and charging decisions are going to dovetail with predictive analytics and catalog-driven approach.. Why? Because predictive analytics are the key to unlocking useful customer insights that can generate contextual intelligence for all customer interactions. With the right data and tools on hand, CSPs can learn about individual data usage and create new policy controls based on the easy-to-launch catalog-driven configurations that offer customers solutions when they need them, revolutionising the way that businesses think about policy, charging, and big data.
Posted: April 18th, 2013 | Author: Juhani Hintikka | Filed under: News | 1 Comment »
Yesterday, we announced Comptel’s financials for the first quarter of 2013. In the first quarter, Comptel’s business developed as per our expectations. Net sales grew 6.2 per cent from the previous year. Especially license sales increased our net sales. Profitability improved significantly and operating result was positive.
Our order backlog growth was also strong. During the first quarter we secured 6 significant orders, valued over EUR 500,000. We also closed a major license deal in Argentina. Market situation in Europe, however, remained challenging.
The outcome of the costs savings that we initiated last year was reflected in our first quarter operating result. Improving profitability is our key target for 2013 and I am pleased that we proceeded in achieving this objective as planned.
We updated our strategy and objectives for the next three years in the beginning of the year. The strategy for 2013 – 2015 focuses on growth by accelerating the execution of the Event-Analysis-Action strategic framework and scaling up the sales with partners.
According to our strategy, we continued investments in R&D in Q1, especially focusing in the service fulfillment automation and in advanced, real-time analytics to leverage the exponentially growing data traffic and services. Both of these focus areas facilitate Comptel’s growth strategy. In addition, we are further developing our integrated software platform which will enable a cost-efficient and solution-based R&D.
To accelerate the strategy execution of analytics, we aligned our organization by centralizing sales, delivery and R&D functions under Analytics Business Unit. With these changes we want to ensure full alignment to our strategy and faster response to diverse customer needs in that field. We seek global Thought Leadership in advanced analytics, which help solve the key business challenges of operators and service providers.
For example in the emerging markets, majority of the end-customers are pre-paid customers. Understanding the behavior of those customers and reading for example early warning signals of in-activity helps operators better meet their customer needs and reduce churn as well as improve return of investments in acquiring new customers.
In mature markets where the data usage is more advanced and the customers are largely invoiced monthly, advanced analytics integrated with Comptel’s other assets such as Comptel Fulfillment and Comptel Policy Control helps operators automate their customer interaction from service provisioning to personalized quality of experience.
Overall, during the first quarter of 2013 we have taken good steps in executing our strategy and the results are beginning to show. We will work persistently to continue the successful execution.
Posted: April 10th, 2013 | Author: Malla Poikela | Filed under: Industry Insights | Tags: 4G, contextual predictive analytics, LTE, predictive analytics | 1 Comment »
LTE use has been following an almost frighteningly fast growth curve. Global LTE traffic is expected to increase by 207% this year, and LTE customers are supposed to double in 2013, surpassing 100 million. Around the world, communications service providers (CSPs) are building new infrastructure to keep up with consumers’ demand for faster data speeds.
The Philippines is no exception – mobile subscribers grew from 6 million in 2000 to 92 million in 2011. By 2016, mobile subscription is expected to reach 117 million people, with a penetration rate of 114 percent.
Since August 2012, LTE has been slowly rolled out across the country, too, covering major cities like Metro Manila, Cebu, Davao, and Boracay. Major CSPs are spearheading the trend. An operator in the Philippines recently announced that it built LTE cell sites to service regions across Luzon, Visayas and Mindanao. And other operators have made similar moves into the LTE space.
Yet offering LTE service and having the right strategy in place to monetise it are sometimes two very different things.
A Demand for Personalisation
Whenever a CSP deploys a new service, the next step is to get people to use it. In the Philippines, we need to consider four big findings among Filipino subscribers who participated in our recent Vanson Bourne survey:
- 84 percent would download more files if they had a better mobile data plan.
- 67 percent top up their phone plans at least once a week.
- 72 percent want personal service when experiencing poor connections.
- 70 percent are likely to pay for a temporary bandwidth upgrade.
- 64 percent have two or more SIM cards
This data shows that there’s not just a demand for the faster data speeds LTE offers, there’s a demand for better, more personalised interaction with CSPs.
Sure, it’s possible to offer customers the same bundled package, but as competition increases, so, too, will innovative pricing packages. In a country like the Philippines, where so many people are topping up every week, it may mean that they’d be open to a new data plan, but they can’t find one that’s suitable.
Yet we see that nearly three-quarters of customers would consider paying for a temporary upgrade. That indicates that if personalised upsells were offered, CSPs could potentially realise greater revenues, because consumers would be willing to take advantage of these special deals.
Adapting for a Country’s Changing Needs
The smartphone phenomenon will change a lot of things, too. Last year, there was a 400 percent increase in demand for smartphones in the Philippines, with penetration expected to grow from 18 percent to 50 percent in the next three years. This trend is going to enable more internet and data use than ever before. One survey showed that more than 80 percent of Filipinos have two or more personal devices, and among that number, 85 percent bring those devices to work.
LTE deployments and a growing acceptance of personal devices at the workplace are going usher in a lot of new changes for CSPs. In short, it’s going to be more important than ever for them to find a way to use the data at their disposal to their advantage.
With predictive analytics, for example, CSPs can analyse their customers, networks and other information, to determine which sets of customers would really benefit from full LTE use and which would most likely only want to use LTE sparingly. This way, promotions can be tailored accordingly, everyone will get the package they want and need, and CSPs can improve relationships in a way that builds loyalty and business performance.
Posted: April 4th, 2013 | Author: Ulla Koivukoski | Filed under: Industry Insights | Tags: analytics, big data, CIQ4T, contextual intelligence, CSP | Comments Off on Three Reasons Why the Telco Industry Needs to Be Thinking about Big Data
At Comptel, we really do believe that data is more than just bits and pieces that can be turned into something truly beautiful. This may seem like a daunting challenge to most communications service providers (CSPs), but that’s why we’re here.
We’ve been doing a lot of work to change that perception—and it’s clear that we’re not the only ones thinking about how Big Data can be a game-changing asset for CSPs. Here are three recent topics that have come up in the news that draw on Comptel’s studies and opinions on Big Data:
1. Flexible Service Packages
As mature markets become saturated, CSPs have to get creative with offers, and one thing is for certain: service packages are going to have to change.
In a recent Computerworld Bulgaria piece, we saw the consumer survey that we debuted at Mobile World Congress highlighted to put more emphasis on this trend.
To recap: our survey found that 49% of consumers chose their current mobile operator because of the service plan, and almost half said they would pay for a temporary upgrade that improved their plan.
The bottom line is that CSPs need to find a way to get the right promotion to the right customer at the right time. Using predictive analytics, it’s now possible to make sense of Big Data and proactively offer the right customers a more flexible service plan that can meet their needs.
In a recent RCR Wireless News report, The smarter telco: Exploring service and network intelligence, Kelly Hill explains that many CSPs are looking for new ways to keep monetizing their services. She points to three specific trends that will have a huge impact:
- The transition to all-IP and LTE networks
- The accelerating trend toward cloud connectivity and network virtualization
- Big Data collection and processing
When discussing Big Data, Kelly cites our research showing that only 27% of operators are currently using analytics on a daily basis, while 33% are using them on a weekly basis.
This could prove to be a disastrous oversight for CSPs. As trends like the shift to all-IP networks and cloud connectivity come into play, analytics that can drive the most value out of Big Data in near real-time is critical for engaging customers and making business decisions.
Big Data analytics isn’t just about finding out what customers need, it’s finding out which customers are influential.
In a recent Financial Times web piece that cited one of our recently commissioned whitepapers, the big message was that, finally, CSPs have the technology to actually use the considerable data at their disposal.
The piece highlights several viewpoints from established telco experts. One of the most interesting points is that, by using Big Data, CSPs can discover which customers are “queen bees.” These are the users who have extensive networks of friends and family. If this particular user leaves his/her operator, then dozens of others could follow because of that influence.
So, it’s best to use Big Data to identify those “queen bees” and find ways to make sure they’re happy.
Continuing the Conversation About Big Data
Most CSPs have Big Data in one form or another, but having it and using it to its full potential are two different things. As this conversation shifts from data to strategy, it’s time to consider how to best operationalize all the valuable information that’s been gathered. In other words, it’s time to leverage Big Data for results.
Over the past few years, Comptel has worked hard for those results to be attainable by offering advanced predictive analytics tools that can automate customer interactions and take relationships to the next level. We’re at the start of an exciting new kind of Big Data revolution. With the right strategy and the right tools, CSPs won’t just have more information for their operations than ever before, they’ll actually be able to do something with it.