It’s a critical period for communication service providers (CSPs). The number of cord cutters dropping their TV subscriptions for OTT offerings continues to gain traction. At the end of Q1 2018, 3.4% of households cut the cord over the prior year, the highest rate ever, leaving 84 million households paying for cable services in the US. This excludes the growing number of new households and younger demographics that have never subscribed to a pay TV service in the first place – “cord nevers”. Currently, approximately 13.5 million households (14% of all households) do not pay for traditional forms of TV service1.
While some might view this news as a forebearer of more bad news to come, others see the opportunity for telecom providers and cable MSOs to stop the cord cutting trend through innovation and also winning over cord nevers. We are a consumption-based society and recent research shows (a) 41% pay for both OTT and traditional pay TV services – and (b) consumers are willing to spend more overall on pay TV if the customer relationships are managed effectively2.
In order for network operators to quickly turn the tide, it will require a deep understanding of their subscriber base. Much deeper than what exists today.
With an improved understanding of each TV subscriber’s viewing habits, it will be possible to grow revenues thru activities such as targeted marketing offers & campaign management, customized product offerings, and deep segmentation analysis. In addition, measures can be taken to lessen churn through exemplary customer service and by predicting those most likely to leave and proactively offering incentives to stay.
For subscribers that have cut the cord and rely only on data plans, it is imperative for CSPs to have visibility into their OTT viewing, web content and download data to determine how to best monetize this use of their network. And operators need timely, accurate metering of data consumption to ensure usage based billing and capped data tiers can capture revenue to best offset what they’re losing from paid TV.
To achieve this deep level of subscriber insight, CSPs require a future-proof analytics solution capable of meeting the massive performance and scale attributes that keep pace with rapid surges in network traffic growth. For example, a mid-sized provider in the US with 1M subscribers can easily need to process more than 1 million records per second, generate tens of billions of daily events and retain petabytes of data generating more than 10 trillion records over the course of 6-12 months.
The default architecture over the past decade to collect network analytics data within operator networks has been deep packet inspection (DPI). Just as it sounds, it either sits in-line with production traffic or sends copies of packets to a network monitoring connection to inspect packets flowing through the network. Information is extracted from within each packet.
While deep packet inspection will likely continue to play a role within operator networks (e.g. traffic engineering), it has many constraints to serve as a viable subscriber analytics solution. First, it’s very difficult and expensive to scale a DPI solution as it relies on inspecting at the packet level, on every port, at increasingly high network speeds. Second, visibility into subscriber activity is limited due to the rapidly increasing amount of encrypted digital media and web traffic delivered on the Internet. Third, it is very difficult to extract insight from DPI systems in that the hardware (physical or virtual) is spread across many points deep inside the network without federation. For a complete view of a customer, or to diagnose a problem, it literally can require hours or days of manual investigation to piece together the various silos of data that exist across separate locations where DPI probes the network traffic.
With major advancements in data analytics infrastructure and storage/compute technology over the past decade, we are overdue for a new scalable analytics architecture that makes it easy to extract insight on a per subscriber basis, dramatically reduces the cost/complexity to implement, and collects/stores data in a passive way that doesn’t involve either invasive probing or copying of production traffic.
Edge Intelligence has leveraged the foundations of our distributed, federated analytics platform to build a turnkey subscriber analytics application capable of meeting the massive scale and performance requirements mandated by CSPs. The system has been designed from the ground-up to be federated across geographically distributed nodes so it is easy to query data and instantly gain all information available for any particular subscriber or group. Passive collection of NetFlow/IPFIX event data is distributed across geographic locations for consuming huge amounts of data at network speed. Multi-dimensional categorization leveraging DNS and DHCP/Radius data is done in real-time to correlate event data with identity information. No specialized hardware is required as software is run on commodity hardware with a small compute & memory footprint for data processing and retention. CSPs have complete flexibility as to how long they wish to retain data within a system that scales to petabytes.
Subscriber analysis and reporting is done using standard SQL commands, data visualization tools and interfaces. Searches are responded to in seconds with patented technology that pre-optimizes stored data for the fastest response to all requests even on the largest datasets exceeding trillions of records. API’s are available to integrate all of the underlying data seamlessly into existing workflows and customer support portals.
Request a demonstration so we can prove to you how we can help you easily gain deep insight into subscriber activities at a fraction of the cost of deep packet inspection (DPI) solutions.
1 – http://fortune.com/2018/03/01/cord-cutting-record-internet-tv/
2 – https://www.digitaltveurope.com/2018/04/05/us-homes-twice-as-likely-to-take-ott-tv-plus-pay-tv-as-ott-alone/
Neil Cohen is the VP of Marketing at Edge Intelligence