Welcome!

Containers Expo Blog Authors: Liz McMillan, Pat Romanski, Yeshim Deniz, Elizabeth White, Zakia Bouachraoui

Related Topics: @DXWorldExpo, Mobile IoT, Microservices Expo, Containers Expo Blog, @CloudExpo, SDN Journal

@DXWorldExpo: Article

Telco Big Data Analytics: Improve Market Share and ARPU

By 2015, Big Data analytics will be one of the critical areas for CSPs to maintain their market-share

It's common knowledge that the subscriber growth enjoyed by wireless Communication Service Providers (CSPs) over the last several years is tapering off. The CSPs really need new sources of revenue to deliver the required growth. Over-The-Top (OTT) players on the other hand are moving quickly into the SP ecosystems and reaching out to their subscribers. To top it all, the regulators are encouraging new entrants and driving prices down. In Europe, regulations for low mobile termination rates and new international roaming charges are impacting revenue and profit for CSPs. The growth of mobile data traffic and the customer demands for better and personalized services are forcing CSPs to invest significantly to upgrade their networks and devices. There are a lot more similar challenges that CSPs face; however, the key point is that the CSPs have to focus on new sources of revenue to augment what they generate from their infrastructure, services portfolio and customer base.

One area where the CSPs have a definite edge over the OTT players is the access to real-time subscriber intelligence. CSPs have a lot of information (read it as Big Data) about an individual subscriber's taste, preferences, favorites, location, their consumption behavior of different voice and data services, service experience, payment history, etc. In addition to the current and contextual subscriber information, the CSPs also have access to a massive amount of untapped historical data (e.g., subscriber and service history) that can be aggregated and brought back into the present to build a richer subscriber profile and identity. The information is captured from different sources in the network at different times using different techniques and, in most cases, scattered across different databases and data warehouses. The CSPs can understand a lot more about their customers and deliver a much more personalized experience by investing in deeper real-time analytics capabilities, leveraging all these subscriber data and deriving to actionable customer intelligence-driven business models (e.g., meaningful products and services).

Analytics improves multiple aspects of CSPs' operations. Terabytes of dynamic customer data will continue to grow exponentially as carriers add new services and as IP-based traffic increases. Big Data is an opportunity for CSPs to create the intelligence for operating a network more efficiently, to analyze the success of the services that CSPs are offering, and to create a better personalized experience for their customers. Big Data analytics enables service providers to better segment subscribers to provide more targeted marketing spend and the insight to predict churn, cross-sell and upsell opportunities, the quality of customer experience and the lifetime value of a customer. The product managers get a better understanding of which services are most profitable, the impact of competitive offerings and the effect of cannibalization caused by a new product roll-out. It also gives network operations the ability to predict capacity issues and the impact of a new service launch.

I have listed below a few areas where wireless service providers can leverage Big Data analytics to improve market share and ARPU (average revenue per user). HP has the skills, experience, products and solutions in this area. HP has combined its business analytics solution with deep telecom networking expertise to help CSPs generate actionable insights for their market growth.

  • Correlate structured and unstructured data from OSS, BSS and Social Intelligence to act in real-time and overcome the complexity of managing networks, services and subscribers across their technical and user experience dimensions
    • Customer Experience Management: offer the best quality of experience to end-users (network intelligence); Gain a single-pane-of-glass visibility into individual user's experience, services and network; Improve the business processes and functions related to customer experience responsibilities

§  Customer experience management combined with policy management and Real Time Billing can improve ARPU and reduce churn (service intelligence) by identifying:

  • Subscribers who need retention activity (e.g., subsidies for new phones, free months of service to compensate for low quality of experience, automated bill adjustments or credits, etc.)
  • Quality of network services (voice/data) and root cause of issues to proactively resolve them and proactively fixing of potential issues for high value subscribers
  • Integration points between OSS and BSS infrastructures for automation and proactive care
    • Service Personalization: Understand customers to deliver personalized services, digital curation-based content, bundles and offerings in real-time; create a smart unified user profile and analytics with a full panoramic and integrated view of the consumer, network and personal data

§  Campaign management: Improve ARPU and customer loyalty through personalized Campaigns

  • Analyze real-time usage to make intra-day marketing program changes, enhanced marketing strategies with real-time analysis
  • Develop marketing strategies when customers are approaching the cap, both for mobile (e.g., provide voice minutes to the preferred number, data traffic only for favorite online service) and fixed BB (e.g., Provide data traffic for preferred video on demand provider)
  • Offer improvement (and up/cross selling) when users engage call center agents
    • Social Intelligence: understand what customers think, improve customer acquisition/retention and create brand awareness, improve & predict sales. Social Intelligence enables organizations to understand and leverage how people behave and what people do on Social Media channels. Social Intelligence is an enabler for many different scenarios:

§  Acquire, retain, and develop high-value customers

§  Reduce value decay and Improving cross-selling rates

§  Optimize communication costs, Improve customer service, manage Customer service crowdsourcing and "owned communities"

§  Activate influencers and enable advocacy

§  Meaning based advertisement

§  Monetize subscribers' base with advertising, couponing and affiliation-based models.

  • Monetize the Customer knowledge and Big Data sssets through advertising and revenue Sharing (e.g., affiliation) business models.
    • The mobile ecosystem is where the service-providers have far more tools and strategies available to engage subscribers and get a slice of the digital advertising market
    • Measure and monitor monetization of campaigns in real time for different business models (from traditional pay per click advertising, enhanced digital Couponing to the end to end digital buyer's journey) through solutions like:

§  Advanced customer profiling (Big Data combining Network, CRM and Social data)

§  Campaign management

§  Advertising marketplace

  • Sharing customer data
    • As the most basic first step Service providers could share their data assets with other big analytics and marketing platforms, to help them build and monetize the data and get a share of the revenues in such a case.

Most of the CSPs are aware of these opportunity areas. To implement any of these use cases, it's important to look at the end-to-end processes, integration points, analytics tools, storage and above all, applying the right logic to derive intelligence out of data. It is my view that many CSPs will start investing this year in Big Data Analytics. Those with dominant market share might start with customer experience management whereas others might start with monetizing the customer intelligence. By 2015, Big Data analytics will be one of the critical areas for CSPs to maintain their market-share.

More Stories By Kapil Raval

Kapil Raval is an experienced technology solutions consultant with nearly 20 years of experience in the telecom industry. He thinks ‘the business’ and focuses on linking business challenges to technology solutions. He currently works for HP and drives strategic solutions in the telecom vertical.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


IoT & Smart Cities Stories
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-c...
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by ...
The explosion of new web/cloud/IoT-based applications and the data they generate are transforming our world right before our eyes. In this rush to adopt these new technologies, organizations are often ignoring fundamental questions concerning who owns the data and failing to ask for permission to conduct invasive surveillance of their customers. Organizations that are not transparent about how their systems gather data telemetry without offering shared data ownership risk product rejection, regu...
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
Predicting the future has never been more challenging - not because of the lack of data but because of the flood of ungoverned and risk laden information. Microsoft states that 2.5 exabytes of data are created every day. Expectations and reliance on data are being pushed to the limits, as demands around hybrid options continue to grow.
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to ...
Enterprises have taken advantage of IoT to achieve important revenue and cost advantages. What is less apparent is how incumbent enterprises operating at scale have, following success with IoT, built analytic, operations management and software development capabilities - ranging from autonomous vehicles to manageable robotics installations. They have embraced these capabilities as if they were Silicon Valley startups.
As IoT continues to increase momentum, so does the associated risk. Secure Device Lifecycle Management (DLM) is ranked as one of the most important technology areas of IoT. Driving this trend is the realization that secure support for IoT devices provides companies the ability to deliver high-quality, reliable, secure offerings faster, create new revenue streams, and reduce support costs, all while building a competitive advantage in their markets. In this session, we will use customer use cases...