OTT and IoT dragging down your subscribers’ QoE?

OTT and IoT dragging down your subscribers’ QoE?


Bandwidth cannibalization is a growing issue among many communication service providers (CSPs). Annual global IP traffic is expected to pass the zettabyte (1000 exabytes, or gigabytes) threshold by the end of 2016, and reach the 2 zettabyte mark by 2019.

This immense volume of bandwidth consumption is being brought on by a number of different sources, and two of the major contributors are over-the-top (OTT) content providers (Netflix, Hulu, Roku, etc.) and the increasing popularity of an all-IP world, or as it’s commonly called, the Internet of Things (IoT).

Consider the Big Picture

OTT – In Q1 2015, Netflix grew its global subscriber base by a record 4.9 million, and now boasts a total base of 62.3 million. Analysts only expect this growth to continue as Netflix plans to aggressively expand in Latin America, Europe, and Scandinavia.subscriber

IoT – The proliferation of IoT is changing more than just CSP strategies; it’s changing the way the world works. Gartner research expects 4.9 billion connected “things” to be used worldwide in 2015, and estimates that number to reach 25 billion “things” by the year 2020.

How are you managing and delivering this data in high volumes at good quality to an increasingly demanding subscriber base?

The cost of network upkeep, paired with a tendency to overestimate actual bandwidth requirements, is leaving many operators with underutilized CAPEX taking up space in their infrastructure plants. At the same time, many operators don’t know what upgrades are required, or when the best time is to upgrade. This results in ineffective spend and increases network congestion, damaging quality-of-experience (QoE) for end-users.

Don’t panic yet. There is a solution.

By utilizing Big Data insights, you can support and offer an abundance of OTT and IoT services without risking your subscribers’ QoE. Internet Protocol Detail Record (IPDR) data collection, which is normally seen as an enabler for usage-based billing, can glean holistic network insights without hindering service performance, and empower network operations and engineering to:

Lower network congestion by increasing visibility into where and when network congestion occurs, enabling the activation of key-performance indicators at congestion points that may hinder QoE

Create and implement fair-usage policies that enforce business actions like temporary speed reductions and throttling for heavy users during peak periods

Effectively split nodes and understand what scenarios work per region and per subscriber to further reduce network congestion

Isolate repetitive top talkers that cost operators more than the revenue being gained

Identify and halt service theft by tracking bandwidth going to and from unclassified or unregistered devices

Analyze geographic and subscriber usage trends to gain a more holistic understanding of bandwidth requirements

Make smarter capacity planning decisions by trending congestion patterns and growth projections

This is just the beginning. Sales and Marketing teams can also monetize subscribers with Big Data as well.


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