Posted: January 31st, 2017 | Author: Malla Poikela | Filed under: Uncategorized | Tags: analytics, customer experience, FASTERMIND, My Digital Moments | No Comments »
Customer experience is the new battleground for telcos. Forrester Research found that 72 percent of companies say that improving customer experience is their top priority. As a provider, if you can engage your customer at the right time with the right personalised service, you have an opportunity to deliver value, establish loyalty and grow your business.
So, what do customers want? To start, they expect full control of their digital life, and the freedom to build their own personal ecosystem of apps and services.
That’s why Comptel launched “My Digital Moments,” a new solution that enables perfect digital customer journeys. With My Digital Moments, customers will benefit from a self-service app on their phone that, in real-time, analyses how they consume digital services. From there, the app can recommend relevant and personalised digital services that would improve their experience.
My Digital Moments opens the door to several value-driving possibilities:
- Service offerings that are proactive, personalised, relevant and contextual
- Increased customer engagement and communication through a direct line to the operator
- Improved engagement by giving customers direct visibility into their plan status and special packages
From the main screen, customers are able to view real-time service usage information, including the percentage of the data they’ve used in this cycle and their data usage trend across specific apps. On top of that, the app can display the operator’s full service portfolio, including new service plans or promotional packages from the portfolio.
My Digital Moments relies on real-time usage monitoring and intelligence from FASTERMIND™ to recommend, predict and automate customer offers based on the most relevant and contextual data. For example, a customer who consumes a lot of mobile data watching Netflix but does not currently have sufficient mobile data could receive an offer for a data plan with unlimited Netflix streaming.
My Digital Moments is also supported by MONETIZER™, which offers the easy and agile configuration of data plans, plus a common platform for charging and policy design. The result puts full control in the hands of your customers, meaning they can self-select relevant, contextual plans or instantly upgrade their data speeds and allocation in the moment.
Of course, new service opportunities can crop up at any time – not just according to your campaign schedule. That’s why My Digital Moments is supported by closed-loop analysis and service recommendations, which means service usage is monitored on an ongoing and real-time basis to ensure your customers are constantly engaged and presented with easy opportunities to get the services they need.
The solution puts the power in the hands of consumers, giving them the opportunity to build their personal digital ecosystems while empowering operators to increase service consumption, reveal new revenue opportunities and nurture loyal, long-term customers.
Heading to Mobile World Congress 2017? Meet with Comptel in Barcelona to learn more about My Digital Moments and our full portfolio of customer engagement solutions. Email firstname.lastname@example.org to arrange a meeting.
Posted: March 2nd, 2016 | Author: Malla Poikela | Filed under: Events | Tags: analytics, big data, customer experience, Mobile World Congress | Comments Off on #MWC2016: It’s Time to Draw Real-Time Value From Untapped Customer Data
This year’s Mobile World Congress (MWC) was another exciting one for Comptel. We launched a new book, Nexterday: Volume II, and Nexterday.org, an online magazine and reader community, threw a party, and met with many operators who were interested in learning more about transforming their business to address the demands of digitalisation, as well as partners, analysts and media. When it comes to effectively transforming to a digital company, one of an operator’s biggest assets is customer data.
A consistent theme throughout MWC 2016 was the idea that operators are sitting on a store of customer data that, like an untapped oil reserve, could deliver rich insights that lead to significant revenue opportunities. Rising interest in the Internet of Things (IoT) isn’t making matters easier – we saw a flood of manufacturers demonstrating their latest connected devices, from cars to wearables, at MWC 2016, plus a fair share of big thinkers promoting their vision for larger-scale, IoT-enabled operations, like smart cities. Here are takeaways from the MWC panel “Operator Customer Analytics,” where those challenges and opportunities were discussed.
The Operator Perspective
Operators have always collected data, but the ways in which they pool, interpret and act on information has changed as technology and processes evolve.
Kuan Moon Yuen, CEO of the consumer group at Singapore-based operator Singtel, explained that his company has developed a more sophisticated analytics estate by pooling insights from multiple data sources. Customer data usage has always been important to telcos, but Singtel stressed that analysing other information – location, device and real-time contextual metrics – allows operators to deliver tailored network optimization, better customer support and predictive, real-time marketing.
Dr. Jiwon Ashley Joo of SK Telecom agreed that context changes the way operators can serve customers. Her company changed its analytics framework to gain a more holistic view of how its customers interact with various services. This type of observation led to service innovation, including a popular new connected wearable device for kids and pets. As these new services are used, the operator collects even more information about its users, which inform future initiatives.
The Standards Association Perspective
Of course, it’s easy enough to point out operators’ need to mine, interpret and act on their substantial data reserves. Rob Rich of TM Forum clarified the challenge by reminding MWC panel attendees of the significant skills gap that prevents many operators from actually putting these ideas into practice.
Of the substantial volume of data currently floating out there in operator environments, a small percentage – about 5 percent, said Rich – is actually actionable. To increase that percentage, operators need to develop an organizational culture for sharing data, and raise their level of sophistication when it comes to leveraging data.
That underscored what’s perhaps the biggest challenge operators face in maximizing customer data: they’re already a bit behind the eight-ball. For digital-born companies like Google and Facebook, a data-centric culture, mindset and competency is already built-in. Telcos need to change to acquire some of those qualities.
The Customer Engagement Automation Solution Perspective
So, if the objectives are to combine multiple insights from disparate data sources, get smarter about how your organisation manages and analyses data and change the culture of your organisation to be more data-centric, what’s your next step?
Third-party partnerships can help operators improve their level of sophistication around analytics initiatives, even democratising analytics insight, so anyone from IT to marketing to sales can make smarter decisions about customer information. Analytics platforms bring together raw data from multiple sources, enrich it to provide context and drive the right actions instantaneously. These solutions enable automated and real-time decisions and actions, helping businesses keep pace with fast-changing buyer needs and wants.
The biggest opportunity here is in real-time and contextual marketing: an operator who learns a customer is running low on mobile data while that individual is listening to a streaming music app has the chance to deliver a highly relevant and compelling top-up offer at the perfect time. It’s how marketing can and should work if you’re able to act in real-time with the right information about your customer.
Learn more about how successful operators leverage customer analytics data in our new book, Nexterday Volume II.
Posted: December 21st, 2015 | Author: Malla Poikela | Filed under: Events | Tags: analytics, internet of things | Comments Off on Digital Disruption in the Physical World: Reflections from IoT World Forum 2015
Walking away from last month’s IoT World Forum in London, where over 400 IoT enthusiasts from various industries came together to exchange views, two major themes were immediately apparent.
First, it was very clear that the Internet of Things (IoT) will be a huge business opportunity for many companies, including operators. Cisco projects that the market for IoT services and technology could generate $19 trillion between 2013 and 2022, while more than 50 billion individual IoT-enabled devices will be connected by 2020.
Secondly, it’s clear we’re moving toward a digital society. Everyone is becoming digitized, and in fact, European operator Tele2 claims that in the IoT economy, all physical things will have a digital twin. And it’s that digital twin which creates digital dependency and product “stickiness” to customers.
What’s the best way forward for operators? How do telcos who have long been focused on connecting customers with traditional voice, messaging and enabling customers’ data access now pursue intriguing new opportunities in an emerging field? Various presenters, a handful of which were operators, at IoT World Forum offered their suggestions – here’s our recap concentrating mainly on the CSPs’ IoT strategies and takeaways.
Find a Good Monetisation Strategy
Ultimately, IoT is about data, and data analytics.
Naturally, operators want to know exactly how they turn all that data generated from those billions of new connected devices into revenue. It was stressed that connectivity is not the only way for operators to earn from IoT, in fact operators need to go beyond connectivity. So instead, telcos must take a service-led approach, relying on connected devices to offer the data that fuels highly personalised and relevant services to customers.
There was an interesting example of an auto insurance provider that defines customers’ insurance policies based on their driving behaviour, which is monitored and tracked by in-vehicle sensors. In this model, IoT-generated data is directly influencing how a consumer service is delivered and priced. Accompanying this behaviour-based insurance model there was a discussion about the other possible alternatives companies might price the IoT, including an ad-funded model, subscription-based model, consumption-based billing, and data trading.
With IoT, the market is moving from CAPEX to OPEX-driven business models, to a ”software as a service” or what one might even call an ”everything as a service” approach.
Find an Innovative Use Case
Operators showcased an amazingly big spectrum of innovative use cases in the field of IoT. These are stretching from various health apps and assisted living to home appliances, smart logistics, smart cities, connected cars and fleet management. Some operators have even made IoT a primary business focus, including one major Tier 1 operator that explained its concentration on the health vertical. To guarantee the best possible success in this domain, they’ve even hired medical doctors to consult on the digitalisation of healthcare.
Build an Ecosystem of IoT Partners
Nobody walks alone in an IoT-driven service ecosystem. IoT market is not be a “one-man show, but rather an ensemble piece.” No single player offers an end-to-end platform that serves a complete array of business use cases.
Bringing all this data together through a compelling ecosystem and service partners, creates a win-win situation for key IoT players. The proposal is to go forward with a culture of experimentation and multi-party models of joint-testing and trials that allow partners to establish proofs of concept and address difficulties before products are released to market, meanwhile applying the well-known principles of “fail fast or scale fast” and “think big, start small and scale fast.”
Address Changing Behaviours to Win Customers
What makes an IoT offering successful? What separates products that are simply hype from those that are genuinely compelling to customers? One conference presenters said “behaviour change is the killer app of IoT,” while another pointed out that the “user is at the centre of IoT.”
There was a common consensus around the popularity of wearable fitness technology. Customers love their FitBits and Jawbones mostly because these devices help their owners become more active. In this case, an IoT device is addressing specific customer behaviour – the desire to live a healthier lifestyle.
Similarly, David Bunch of Shell asked whether today’s youth – more of whom view cars as functional appliances rather than an aspirational purchase – cares much at all about owning their own vehicle. As a result of this changing behaviour, Bunch argues that it’s more a question of when, not if, connected autonomous vehicles will roam city streets as the preferred method of transportation.
Unlike discussions that position the IoT as a sort of futuristic piece of science fiction technology, the tenor of the conversation at IoT World Forum focused on real, pragmatic solutions. For operators, the way forward involves service-led business models and creativity pricing, the creation of beneficial partner ecosystems, establishing innovation labs and a priority on IoT-enabled services that serve evolving customer behaviours and desires.
Download our book, Operation Nexterday, to learn the strategies and solutions that help mobile operators innovate their service offerings and intrigue Generation Cloud consumers.
Posted: October 19th, 2015 | Author: Veli-Pekka Luoma | Filed under: Industry Insights | Tags: analytics, cloud, Comptel, innovation, start-up | Comments Off on (Working) Life at an Internal Start-up
The start-up life is interesting anywhere, but especially so when you’re working at an internal start-up.
Comptel’s A.I.R team has been working hard to create a cloud-based SaaS analytics offering, and get it technically and commercially tested in the market. Development work has been successful; we are just about to go out with A.I.R’s second release, called Intelligent Monitoring. Together with our previous release, Critical Alarm Prediction, we are now able to process cloud analytics in a way that’s easily scalable, adaptable, automated and convenient in many use cases.
Starting with improving maintenance processes in networked environments, A.I.R’s capabilities can be implemented in various situations where plain data needs to be turned into information, information turned into knowledge, and finally, knowledge turned into decisions and actions.
These solutions that we’ve developed within our internal start-up are expanding Comptel’s offerings and making them future-proof. For instance, A.I.R has added virtualization, capacity balancing, and flexible access to resources, technology and competencies to Comptel’s portfolio for its current and future customers. After all, any offering today without cloud-based capabilities may as well be deemed pre-historic. We have already used our solutions successfully in several proof of concepts, too.
The DNA of a typical start-up includes a strong element of focus. Results must be sharp and precise, answering the customer and user needs exactly and quickly. Though start-ups lack the support and power of larger organizations and their ready-made processes, the benefit of having a start-up mentality is the ability to react and execute fast.
The potential to scale up a start-up business is often limited, but it depends on the product. If the product is fully digital, rather than reliant on a physical system, then the scaling is possible for even the smallest teams and organizations.
Looking ahead, we plan to adapt cloud-based capabilities into more of Comptel’s offerings, including its Intelligent Data offering. And with our customers becoming increasingly active in the Internet of Things, we’ll be looking to produce automated processes for connected, intelligent systems across all aspects of life.
In everything we do, innovation is the goal. Our mission is finding ways to not only improve our customers’ business, but also to drive the technical evolution of our surrounding world, from housing and health to transportation, security and production. “Innovation” is not simply a buzzword – we encourage everyone to use and execute it daily. Big innovation might get noticed, but it’s usually the small and even invisible innovations that keeps us moving ahead and beyond.
Posted: April 2nd, 2015 | Author: Mikko Jarva | Filed under: Industry Insights | Tags: analytics, big data, intelligent data, machine-learning | 1 Comment »
For some digital and communications services provider executives, the Big Data trend has been a big disappointment. Operators were entranced by the idea that rich data analysis can reveal targeted insights that drive more revenue, but not every telco has seen its analytics investments turn into real business results. That has created some noticeable Big Data frustrations.
Research firm Gartner tracks market enthusiasm for emerging technologies with its “Hype Cycle,” and last year, Big Data moved from the “peak of inflated expectations” to the “trough of disillusionment.” While that sounds bad at first glance, it really means that businesses are moving beyond the stage of unrestrained expectations and instead starting to ask practical questions about how Big Data can actually solve their problems.
This more realistic view of Big Data means that when a project falls short of expectations, results-oriented executives may be less forgiving of the entire premise. But, is a lack of ROI an indictment on data analytics as a whole, or is it more a reflection of poor execution?
At Comptel, we argue it is the latter. As my colleague, Malla Poikela, wrote in a recent piece for LinkedIn Pulse, the most common hallmarks of a poor-performing Big Data initiative include difficulties accounting for every new raw data source and then turning all of that data into real-time contextual decisions and actions.
Successful programs rely on relevant actionability. Relevance comes from identifying contexts in real-time data, implying specific needs and employing predictive analytics to optimise target selection for those needs. Actionability is achieved through an end-to-end, integrated, real-time process that connects data streams through analysis to action.
It’s not about Big Data. It’s about Intelligent Fast Data, and it’s the only way to treat information at a time when technology empowers consumers to make informed buying decisions faster than ever and complexity grows in multiple dimensions simultaneously.
What are the benefits? With better understanding of existing customers and their preferences, operators can cue up the personalised service offers that customers want at exactly the right time on any device. It’s real-time marketing, driven by in-the-moment analysis, which leads to instant revenue opportunities.
More generally, Intelligent Fast Data can be considered a process that constantly monitors various forms of digital demand and connects that demand with available digital supply, be it a subscriber needing faster bandwidth temporarily to watch a video on demand, a network requiring additional capacity from virtualized packet core functions or supplying a service desk with a data feed from temperature sensors in a connected home.
Here’s how operators can start to make the switch from Big Data to Intelligent Fast Data.
Think Beyond Rules-Based Parameters
One of the downfalls of traditional decision-making system implementations has been a sole reliance on rules-based infrastructure. This form of analytics provides recommendations based on a set of pre-determined rules, but the challenge is that such a system might not be very accurate and can become overly tedious to manage as the number of rules increases. Rules or logics are important decision-making capabilities, but just like in human decision-making, they often need to be supplemented with capabilities such as pattern matching, predictions and anomaly detection. Intelligent Fast Data enables just that: the embedding of machine-learning-driven advanced analytics capabilities into decision-making.
If Insurance, a property and casualty insurer, took this approach to revamp its insurance claim analysis. If stepped up its automation capabilities with an Intelligent Fast Data system, which automatically learns patterns of insurance claims and flags normal claims for automatic processing, while highlighting potentially fraudulent or anomalous claims for further inspection. With the Intelligent Fast Data system the company was able to further reduce manual claims processing work and triple its number of accurately processed claims.
By embracing Intelligent Fast Data (i.e. decision-making automation with embedded analytics), digital and communication services providers can speed up and enhance the process that turns their data streams through analysis and targeted actions into new revenue streams.
Eliminate ‘Data Wrangling’
Another obstacle that could be holding back your switch to Intelligent Fast Data is a phenomenon known as “data wrangling.” According to the New York Times, data scientists can spend 50 to 80 percent of their time and talent essentially prepping data for the analytics process. It’s busywork, and it means you could be taking far too long to turn customer data into action.
To eliminate time-consuming data cleansing and enable faster time to action, a flexible and agile data processing layer is required, particularly one with the ability to integrate information from any digital source, then automatically cleanse, normalise, enrich and transform the data into ready data products and actions, which are consequently delivered to the systems with specific demands. Such a data processing layer must have smart adaption capabilities so that is able to cope with changes in data streams and the addition of new ones without data wrangling.
Remove Purchasing Friction
Changing how you integrate and process data is step one to drawing more value from Intelligent Fast Data investments. However, operators also need to eliminate any potential roadblocks to realising revenue from the insights data provides. This sometimes requires creative solutions.
For example, Indosat, one of Indonesia’s top mobile operators, needed to find a way to monetise mobile revenue opportunities in a country with one major roadblock. Despite being home to more than 250 million residents, only 8 million people in Indonesia have credit cards. That’s 3.3 percent of the population and 7.7 percent of the country’s sizeable base of smartphone users.
Smartphone users in Indonesia can’t simply purchase apps and services on their phone from a stored credit card like consumers elsewhere. However, a creative solution – direct carrier billing for the Google Play store – enabled Indosat to offer its consumers the same purchasing experience smartphone users worldwide enjoy.
Removing this obstacle opened up a new revenue channel for Indosat, and as the operator collects customer app usage data, it will be able to refine this information into insights and actions that drive even more financial benefits.
Intelligent Fast Data, ultimately, allows operators to profit from a wealth of Big Data.
Want to learn more about how Intelligent Fast Data can help you draw more value from new and existing customer relationships? Download our new book, Operation Nexterday, for expert research and insights.
Posted: November 21st, 2014 | Author: Leila Heijola | Filed under: Events | Tags: analytics, APAC, big data, conferences, data fastermind, Events, loop apac14 | Comments Off on A Recap of LOOP APAC14
Last week at LOOP APAC14, communications service providers came together to discuss the future of the telecommunications industry and how new tools and developments can help spur innovation and disruption. The team at Comptel – along with representatives from Salesforce.com, Tech Mahindra and GE Smallworld, offered insights into what CSPs can expect next year and how new kinds of technologies will help revolutionise networks and customer experience.
We put together a collection of tweets to help show the highlights of the conference:
Posted: October 27th, 2014 | Author: Malla Poikela | Filed under: News | Tags: analytics, eventlink, mediation | 4 Comments »
Few businesses have as much constantly streaming data as communications service providers (CSPs). Day and night, seven days a week, customers are sending and receiving huge amounts of data. The amount of data in flux is not just growing, but it also comes in different formats, varying from structured to unstructured, real-time and historical.
That’s a lot of information to process and manage. Over time, the constant flow of data across technologies like fixed, mobile, IMS, LTE, cable and IPTV has resulted in siloed, fragmented data sets. These scattered data processing layers require not just consolidation but also intelligent data analysis capabilities to turn every grain of insight into value and revenue for the operator.
To solve this situation, Comptel is bringing a new version of its convergent mediation platform, Comptel EventLink 7, to market. The market is ready for a new era of mediation that streams and refines data into automated, intelligent actions such as upsell campaigns, roaming data, targeted customer lists, cloud orchestration and charging, as well as offers real-time early warnings for xDR anomalies, multi-country data consolidation, LTE/VoLTE services management capabilities and more. Comptel EventLink can provide that technology.
With a new kind of mediation software, CSPs will be able to increase time-to-market, operational efficiency, advanced monitoring, service forecasting and real-time customer engagement. Here’s how.
A Data Refinery that Integrates, Learns and Turns Data into Action
Comptel EventLink 7.0 connects all the dots across devices, applications, network elements, customers and locations, collecting and intelligently analysing streaming data. Comptel EventLink ensures that data is in the right place at the right time, capturing contextual information and formatting it for delivery to the destination engine.
This “data refinery” smoothly integrates and embeds analytics to the mediation layer, and consolidates all the data coming into and being sent out of it. That ensures that no information is lost. CSPs can maximise and control every last bit of data in its native format, including the access to the unfiltered raw data, across every operation.
Comptel’s new Big Data mediation software, Comptel EventLink natively integrates and embeds analysis, reporting and machine-learning capabilities, allowing operators to use the contextual intelligence from that Big Data to speed up business decisions and actions.
For example, operational intelligence empowered by a data refinery can stop revenue loss and identify unexpected traffic peaks while improving Quality of Service. Simply by collecting historical and real-time data, a data refinery can provide operators with a snapshot of what to expect in the future and send alarms about any potential service peaks or disruptions.
Without a data refinery to process all that streaming data, CSPs could be missing out on a lot of “sleeping” revenue or insights. If xDRs aren’t analysed, predicted and monitored in real-time, revenue loss, service disruptions and anomalous patterns can get completely overlooked. A data refinery integrates, refines and learns from the information traveling back and forth on the network, alerting CSPs about upcoming issues and opportunities.
A Superior User Experience
So how can CSPs make the most of the Comptel EventLink data refinery? By building workflows around how the data gets used. In order to help businesses efficiently leverage data streams, Comptel has researched CSP users’ end-to-end business design journeys and translated the invaluable learnings into our new user experience (UX) interface.
The result is the Comptel EventLink Stream Designer. With an intuitive, drag-and-drop dashboard, the Stream Designer allows CSPs to build new products and services cost-effectively, quickly and easily. Stream Designer is a revolutionary new way for CSPs to configure how data is managed and used.
In addition to offline streams, active, online streams are fully supported, so it’s possible to build a workflow that intelligently streams online data or monitors customer’s data usage across a network and automatically sends that information to the relevant destination, business or operations team.
With a sleek, user experience and interface to build custom workflows, Comptel EventLink is ushering in a new era of mediation. The timing couldn’t be better. With the Internet of Things promising a world of connected watches, cars, refrigerators and more – along with the exponential growth in data use – contextual, real-time analysis and reporting is increasingly becoming a business-critical initiative. A data refinery that can perform real-time, automated analysis and speed up intelligent decisions and actions will enable CSPs to continue innovating, building customer loyalty and optimising their business.
Want to try out the next generation of mediation? Learn more about Comptel’s new convergent mediation platform or download our EventLink 7.0 presentation below.
Posted: August 12th, 2014 | Author: Max Nyman | Filed under: Industry Insights | Tags: analytics, big data, contextual intelligence | Comments Off on A Scarlett Johansson Movie Shows How Analytics Can Make Data More Human
When we traditionally think of data, we think of reams of numbers and not much else. It’s a pretty cold definition, a combination of ones and zeroes that help us stay organised. Companies are starting to leverage their data for all sorts of new business applications.
In the telecommunications sector, that’s often contributed to delivering a better customer experience and supporting more informed, strategic decision-making.
The problem with data is that you need to pore through back-office systems to find what you need.
Data can help optimise processes and build revolutionary new services, but it’s long been up to the humans on the back-end to sort and process the information in a way that makes sense for the business. That’s changing. As machine learning becomes more sophisticated, that technology can be applied to data, creating a system that can learn what the company needs and deliver that information in real-time.
Oddly enough, one of the best illustrations of these capabilities was in a Scarlett Johansson movie. Raj Amin, co-founder of Mana Health, recently wrote that the movie “Her” showed a glimpse of how data can adopt a more human-like context.
Making Data Come to Life
In “Her”, Johansson plays an artificially intelligent operating system. The scene that Amin highlights is when she helps the protagonist, Theodore (played by Joaquin Phoenix), sort through his emails. As he’s directing the process, Theodore adds that he thought some of them might be funny and – lo and behold – Johansson laughs and saves the emails that she thinks are amusing.
Amin points this out as a great example of how data can become more human and, therefore, a lot more meaningful to the people who are using it. By analysing emails and then adjusting the query based on what Theodore really wants, Johansson is connecting with Theodore not just through process, but through real-time, human-like learning.
At Comptel, we’re working hard to help ensure that automation, predictive analytics and Big Data have similar powers by applying machine learning to all the information being processed. Just like the operating system voiced by Johansson, our machine learning can make use of the data that companies already have and make automatic, contextualized recommendations. That’s the foundation for our business application, Critical Alarm Protection (CAP), for example.
CAP helps communications service providers predict and prioritise network issues and site failures before they occur. Just like in “Her,” CAP can provide rankings and recommendations for different actions. If there’s potential for an outage at a specific site, CAP automatically sends a notification to the operations team, with suggestions on how to fix the problem.
When data is combined with machine learning and automation, it really is possible to make numbers feel more human. Rather than digging through data for the answers, new applications like CAP can sort through the information and suggest the right solution for you. It might not quite be like having a fully sentient operating system, but it’s a step in the right direction.
If you want to learn more about what CAP’s predictive, contextual powers can do for your business, check out our informational page, or register for our webinar on 15 August.
Posted: March 4th, 2014 | Author: Leila Heijola | Filed under: Events | Tags: analytics, big data, Mobile World Congress, mwc 2014 | 1 Comment »
Mobile World Congress 2014 broke all the records of the previous year. With more than 85,000 visitors and 1,800 exhibiting companies in Barcelona, the event saw quite a bit of fanfare. Comptel was at MWC all week and we enjoyed being right in the middle of the action.
From Big Data to smartphones, connected cars to connected refrigerators, Mobile World Congress 2014 showed us a glimpse of what we can expect this year… and next year and the year after that. As a final recap, we decided to comb Twitter and see what topics had caused the most excitement.
Want to learn more about telco in 2014? Download our new eBook, “What Telco CMOs and CTOs/CIOs Are Thinking in 2014.”
In this eBook, we share exclusive, global executive research that highlights:
– Executive strategies for 2014
– Barriers to integration
– Technology priorities
– Attitudes toward data & planning
Posted: January 17th, 2014 | Author: Leila Heijola | Filed under: Telecom Trends | Tags: analytics, big data, CDRs, CSPs, Storify | Comments Off on How Telcos Can Benefit From Big Data Analytics
Big Data has been, and continues to be, one of the buzziest terms in the tech world. Big Data analytics are essential for separating important customer and business information from the rest of the data. The contextual intelligence gleaned from Big Data analytics can, and should be, an important consideration for any business decision CSPs may make.
By examining customers’ social behaviours, such as call detail records (CDRs), how frequently they place calls outside of their networks, etc. CSPs can develop targeted, relevant marketing campaigns that simultaneously reduce the likelihood of churn and create new business opportunities. Of course, this is only one example of how Big Data is reshaping the way CSPs, and other companies for that matter, do business. Just take a look at what people in the Twittersphere are saying about Big Data’s future.
Comptel has pulled together some recent developments for Big Data analytics below. Enjoy!