It’s Back: Telecom Merger Mania – The Top Ten Ways to Use Big Data in Mega Mergers
With AT&T’s announced merger with Time Warner, Verizon’s announced acquisition of Yahoo’s network business plus XO’s fiber network, Windstream’s plans to purchase Earthlink and CenturyLink’s announced purchase of Level 3, the Telecom Industry’s merger mania is back with a vengeance – over $127B in deals announced in the past 8 months. And more are likely on the way.
Taking a closer look at the largest merger (and likely the most controversial) – AT&T’s CEO states its merger with Time Warner is designed to “get the most content to the most people at the lowest prices delivered on any screen, particularly mobile.”
Many, including my hometown paper, the Chicago Tribune, support this ‘Vertical’ merger. In an October 24, 2016 editorial it stated “Trends in the digital world are moving in the direction of giving more options to consumers, not fewer. Good.”
Both AT&T’s CEO as well as The Chicago Tribune’s editorial agree on one thing: The merger is designed to enable AT&T to compete head-to-head with cable operators using 5G technology – and it aims to disrupt long-established distribution channels.
But how do you make these mergers successful? Certainly vertical mergers may have greater challenges than horizontal mergers. Vertical mergers are geared to provide new and interesting bundles and services to customers – to satisfy their appetite for content and bandwidth.
Yet, even the FCC has recently weighed in with proposed rules to require Internet Service Providers to ask permission of their customers to collect and use personal information such as Web browsing history.
So how do you design the right bundles of services that will be attractive to customers when you are hamstrung by such onerous FCC regulations?
Job 1 is to turn this restriction into an advantage: Promise your customers a bevy of benefits if they allow access to this information and use it – both anonymously to help design new services as well as specifically to help improve a customer’s individual service.
With the above as a backdrop, here are my Top Ten Ways to Use Big Data in Mega Mergers:
- Suggest new content based on a customer’s mobile viewing habits, with a preference to content produced by internal business units. For Example: Verizon offering content from The Huffington Post.
- Automate the suggestion of new content based on a customer’s mobile application usage, such as location and recent purchases via mobile apps.
- Leverage data analytics to identify and upsell customers to customized usage plans as they approach monthly plan limits.
- Provide customized choices, content and service options in real time to your high value customers as determined by their total lifetime value across an entire vertically-integrated business. For Example: AT&T offering customized bundles to DirecTV customers based on customer longevity.
- Develop new offers focused on micro-segmentation of customers – also across an entire vertically-integrated business
- Provide upgraded ‘white glove’ customer care in case of network problems for your high value customers. One example of ‘white glove’ service is a proactive notification to a high value customer of an immediate credit to their account within seconds of a dropped wireless call or data connection.
- Provide more customized options in real-time for consumer credits in case of network problems for high-value customers. Examples could be a wide range of choices from (standard) bill credits to customized options of free upgrades to high usage tiers, free music downloads or a free episode of a favorite show. The last three options would be customized to their specific recent usage history.
- Implement Item 6 above to reduce Operating Expense (Opex). The proactive, automatic treatment of high value customers reduces calls to your call centers by 15% – and correspondingly reduces your Opex.
- Implement an integrated application infrastructure for rapid and low cost establishment of the Big Data analytic environments needed to support items 1-8.
- Implement an integrated IT service catalog (with easy provisioning of Big Data sandboxes, for example) plus a standardized, modern operating model. In this way, businesses within the merged company can continue to choose and pay for IT services that they need – but efficiencies lead to an overall lower Opex.
Okay, so the last two items are not strictly Big Data – but they provide a foundation for the rapid implementation of Big Data analytics environments necessary for items 1-8. Dell EMC’s experience in working with clients that once you’ve identify the right use cases for analytics the biggest challenges for Big Data projects is the rapid access to analytics environments and data sources to ingest.
Everything I mentioned above is pragmatic and achievable with a solution of Big Data Analytics operating on data ingested from many sources within a Telecom company as well as external sources plus actions taken on an individual customer basis. In addition, transformation of the disparate IT infrastructures and operating models lead to significant Opex and Capex savings for the enterprise. And many of the above techniques are already in production around the world using Dell EMC solutions.
Want more information on how to grow revenue and reduce Opex and Capex with the above techniques? Please contact me!
Next Up: Network Function Virtualization – Myth or Reality?
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Today’s Travel Tip: Vacation in Puerto Rico – For American’s (like me) it’s like going to a foreign country, excepts it is not (a foreign country, that it), and for the international traveler it is a hidden gem.
- Great beaches all around
- Old San Juan has plenty for any history buff
- The average temperature is 70-80F (or 21-26C)
- There is an endless supply of rum
- For Telecommunication geeks and movie buffs, take a ride to the Arecibo Radio Telescope Observatory – and take the ‘VIP Tour’ if it is offered. Even if it is not, you’ll enjoy seeing and learning about the cutting edge science that takes place here. It’s much more than what was shown in the 007 movie GoldenEye. I had a great time –as shown in the photo below.