Data Monetization: Make the Most of Your Most Valuable Asset

Dec. 7, 2016
The very devices and applications favored by subscribers today are also a goldmine of data. This information could be your company's most valuable asset — but few providers are maximizing this resource to its full benefit. Focusing on data monetization while still respecting subscriber privacy is possible — and necessary — to stay afloat in an increasingly competitive market.

The number of connected devices per household is higher than ever before. Recent forecasts estimate that more than 1 billion new Internet users are expected to join the global Internet community in the near future, growing from 3 billion in 2015 to 4.1 billion by 2020. Meanwhile, global IP networks will grow by an additional 10 billion new devices and connections in that period.

For communication service providers, this presents a conundrum — subscribers' increasing appetite for IP-based applications is driving bandwidth usage and causing network congestion, which leads to poor quality of experience (QoE) and/or expensive network upgrades. But could such changing subscriber habits also offer service providers an opportunity?

The very devices and applications favored by subscribers today are also a goldmine of data. This information could be your company's most valuable asset — but few providers are maximizing this resource to its full benefit. Focusing on data monetization while still respecting subscriber privacy is possible — and necessary — to stay afloat in an increasingly competitive market.

For cable multi-system operators (MSOs), Internet Protocol Detail Record (IPDR) collection is the most effective mechanism for gathering per-subscriber service usage information directly from the CMTS. This information provides details on network topology, service flows and, most important, bandwidth consumption details about every subscriber device on the network without overstraining hardware.

When combined with SNMP data, a full breakdown of valuable network data opens up a comprehensive analysis of subscriber QoE, enabling providers to pinpoint with accuracy which interface, node and service group traffic comes from; how much bandwidth is used; the maximum throughput; and network congestion points. In telco or converged environments, device usage statistics and subscriber data may also be gathered through other technology or protocols, including the Broadband TR-069, SNMP, AAA records and technologies like virtualized customer premises equipment (vCPE).

Whatever the method of data extraction, the challenge comes with extrapolating trends and using raw data to generate revenue. Big Data is extremely valuable. This information has potential for monetization in every department of a modern communication service provider, from engineering, operations and planning, to marketing and sales. For example, operators can use subscriber and network data to enable:

  • Real-time bandwidth congestion management for better customer QoE. You can't manage what you don't measure. Find out exactly where and when bandwidth is being used on your network to improve the subscriber experience. With the right tools and visibility, you can use data to manage bandwidth congestion in real-time to improve customer QoE in peak periods.
  • Effective network capacity planning and forecasting to cut unnecessary operational expenses. Analyze subscriber growth and bandwidth use habits to predict future trends, such as saturation of interfaces and nodes. This enables you to base investment decisions such as regional upgrades or equipment replacements on real data. Create new metrics and priorities for node splits, upgrades and policy based on subscriber concentration, subscriber type and percentage of premium subscribers on the node.
  • Identification of heavy users and premium subscribers for network improvements and new revenue opportunities. Bandwidth is a shared resource and the consumption practices of excessive users often hurts the quality of service for other subscribers, not to mention increasing the cost of network investments. Use data to isolate key, repetitive heavy users that cost more than revenue provided; use traffic patterns to identify better distribution of capacity needs. You can also identify premium subscribers and correlate information about network congestion to see whether upgrades should be prioritized in a particular area to meet service-level agreements.
  • Creation and enforcement of fair use policies such as usage-based billing. Identify peak usage periods, congestion points and heavy users to enforce business policies — such as temporarily throttling down heavy users during peak times — to guarantee fair use of resources. Drive revenue with usage-based pricing and tiered options to give subscribers the option to migrate to higher speeds or greater bandwidth quotas if they are willing to pay more. Bandwidth caps are already a fixture of communication service providers, and the shift from unlimited to capped data plans has enabled greater competition and more choice for consumers.
  • The implementation of network-wide or targeted revenue-generating policies, up-selling and tailored promotions. Visibility into usage habits and trends makes it easier to understand what new products should be offered, and to whom. Identify when a customer should be offered different media access or a different package, or a trial upgrade to better suit their usage based on bandwidth utilization history, traffic hours, traffic type and subscriber type (business or residential). A small or medium-sized business may have different needs than a residential subscriber — for example, a hotel may be interested in a new service, such as higher upload capacity with lower latency, to improve quality of service and reliability for their guests. Understanding usage data enables smarter marketing and sales strategies and the ability to successfully plan revenue-generating opportunities for the future.

The hardest part for most service providers in achieving these benefits is finding, tracking and making sense of the increasing amount of available data. Today, it is more vital than ever to filter and analyze raw data to make sense of current network status, forecasts, and subscriber behavior to uncover under-used resources, plan for the future and strategize for new revenue opportunities. Without the ability to find and analyze the information hidden in your network, you risk customer attrition.

Revenue streams are shrinking while the cost of network upkeep continues to grow. Increasing average revenue per user (ARPU) in a competitive market is always a challenge. But through the insight contained within subscriber data, operators have an opportunity to offer value-added services, bundles and tiered pricing levels to cater to the different needs of subscribers and generate new revenue.

Pete Koat is the chief technology officer for Incognito Software Systems. Pete has more than 15 years of experience in executive management, project management, software development and architecture, embedded devices, network protocols, system integration and hardware design.