Email a colleague    

June 2013

Analytics Biology: Evolving to New Data Sources & Intelligence Gathering Methods

Analytics Biology: The Power of Evolving to New Data Sources and Intelligence Gathering Methods

“Two roads diverged in a wood, and I --
I took the one less traveled by,
And that has made all the difference.“

Robert Frost, American Poet (1874-1963)

In analytics, the well-trodden path is certainly the Teradata data warehouse.  The Teradata DW, the standard at most large telecoms, is as useful and powerful as ever.  But does that mean we should sacrifice a hundred fast ROIs for the comfort level of saying we have a “single version of the truth”?

No, it’s time for DW champions to fully bless value-creating solutions not invented or controlled by IT.  If there’s advantage to be gained from third-party big data platforms, bring them on.  Let those platforms fight for the budget dollars to extract value from the countless pockets of operational efficiency that have yet to be fully explored.

Over time, Charles Darwin’s laws will surely play out: the many species of big data beast will get pared down to a few robust survivors like the crocodile, horseshoe crab, and duck-billed platypus.

And while we’re at it, it’s time to look beyond the tried and true data sources and intelligence gathering methods of the past.

Here to help evangelize that vision is Paul Morrissey, Chief of Strategy and Business Development of analytics software firm Ventraq.  Paul’s perspective draws from his long career in telecom and in related fields like military intelligence and the mobile gaming industry.

Dan Baker: Paul, what is it about the way telecoms operate that frustrates you the most?

Paul Morrissey: Dan, I’ve been in the global telecom business for 30 years and a perennial concern of mine is that carriers have never been that close to customers.

To be honest, I thought that carriers were fairly arrogant in the way that they treated customers.  They didn‘t value them correctly.  Sure, they valued them as blocks of subscribers, but not as individual assets.

Thankfully these things have changed in the last 18 months now that we actually have the capability to know a customer’s likes, dislikes, buying habits, trends, associations, and other customer attributes we either didn‘t value or thought were too costly to go after before.

You should feel fortunate then.  Now that you head up the Big Data program at TM Forum, you no longer need to be a wolf howling in the woods.

Yes, working with TMF is feeding my passion for figuring out how telecoms can really move forward with big data.  And the first project I put in place there is something called the Customer Experience Management Index (CEMI).

Up to now, a telecom’s view of CEM has been rather fragmented.  It’s measured in many things: network quality, customer service, customer billing accuracy — and I thought this paradigm was wrong.  So I proposed we should instead measure CEM across the whole of the enterprise and come up with a business index rather than a technology index.

And that is what the CEMI is about.  It’s a global standard in the form of index that measures one carrier against another.  We started with a Catalyst on the idea, but now we actually have a written specification for CEMI in the TM Forum environment.

Then there’s the position you hold as Chief of Strategy at Ventraq.  Where’s Ventraq headed these days?

Well, you can bet that Ventraq is doubling down at empowering carriers to gain a more in-depth view of their customers‘ experiences.  One measure of that commitment is the sheer volume and number of data sources they ingest.

One carrier customer is taking 10 billion records a day into their Ventraq database.  And that data is multi-faceted.  It not only includes the B/OSS and network data you’d expect.  They also take in third party reference data and GPS positions.  They track: the smart phones the customers have; how those smart phones are used; what websites the customers visit; and how influential each customer is with other people in their network via social media, such as Facebook and Twitter.

Years back, CEM was a matter of looking at things like the call center to determine service satisfaction.  Now this is a valid piece of information, but there are many of other pieces of information that can be used as well.

So if you look at the last 100 customers who churned from your mobile network, and you have a set of attributes they all share, you can run those attributes against the rest of the customers and see how close they are to getting to churning as well.

What they are trying to do is break down the silos of where that data comes from and harmonize it into a single database with a 360 degree view of the customer.  That is what Ventraq aims to do better than anyone else.

Can you give us a couple examples of where a 360 degree view of the customer adds value?

One great example is the single-minded focus on a higher ARPU as the all-important business driver.

But imagine if one of the low ARPU customers you serve is the CEO or CFO of a company that you are providing global services for.  That customer suddenly deserves special VIP treatment, but if you are only looking at ARPU, you miss that perspective.

Now the only way you can figure out who the key influences are within those organizations is with large data management.

Here’s another classic example.  You are measuring call answering time on IVR or call answering time on a phone or you measure the frustration of people going through an IVR system, and then you ask the customer at the end of the call if they are satisfied with their service.

I use Skype and I’ve noticed that every time you make a Skype call, they ask you to rate the call.  When you finish the call, it asks you to grade the service 1,2,3,4, or 5 points.  Now a lot of people don‘t answer that Skype survey, but that’s an important detail too because it generally means the caller is more or less satisfied.  Now I can tell you that many carriers don’t have such a survey.

So these are the kinds of services that Ventraq focuses on it.

Tell me more about using social media.  I’m one of those who believes the noise to signal ratio of social media makes it one of the less valuable data sources to track.

Consider this, Dan.  The incremental cost to capture and analyze social media is so low that it can still deliver insights even if CDR analysis remains a more valuable source overall.

For instance, Ventraq has a system that measures each Twitter tweet.  Yes, that feed is very much of a fire hose, but you can still do some interesting things with it.

You can count how many times a telecom is mentioned in Twitter and measure the percent of positive or negative tweets.  It’s called sentiment analysis, and it’s based on keywords.  Now, where the data sets get more interesting is when you group the tweets by geographic location and learn that in New York, customers of Carrier A are more satisfied than customers of Carrier B.

Paul, I understand you also have a background in gaming and military intelligence.  What’s that about?

Well, I am chairman of a gaming company called Lucid Games.  And in the gaming business one of the techniques is to push information and cultivate the key influencers who advocate and tell others about your game.

And yes, I’ve also been involved in military intelligence.  So I’m eager to see some of the analytics principles in the gaming and defence world applied in telco.

One powerful technique uses an email extraction tool that lets you see groups of people who send emails to each other.  The idea is to send an email message to 100 people and ask them to forward the email to others.  If everything works well, the network will eventually send an email back to you.  In any case, the point is to analyze the flow of messages across the network to see who is connected to whom.

Thanks, Paul, it’s a safe guess that big data will pave the way for lots of novel data sources and techniques, including stuff that hasn‘t even been dreamed up yet.

Copyright 2013 Black Swan Telecom Journal

 

About the Expert

Paul Morrissey

Paul Morrissey

Professor Paul Morrissey is Chief Stategy and Business Development Officer at Ventraq.  He is a technology entrepreneur with 30 years of experience in fields such as advanced data centre, telco operational systems, security, and forensics.

In 2010 he was awarded a professorship by the School of Mathematics and Computing at Liverpool John Moores University for work surrounding university technology spin-out companies.  He is head of the Data Analytics Group at TM Forum and has been associated with Ventraq for over ten years.   Contact Paul via

Related Stories

  • A Big Data Starter Kit in the Cloud: How Smaller Operators Can Get Rolling with Advanced Analytics interview with Ryan Guthrie — Medium to small operators know “big data” is out there alright, but technical staffing and cost issues have held them back from implementing it.  This interview discusses the advantages of moving advanced analytics to the cloud where operators can get up and running faster and at lower cost.
  • Telecoms Failing Badly in CAPEX: The Desperate Need for Asset Management & Financial Visibility interview with Ashwin Chalapathy — A 2012 PwC report put the telecom industry on the operating table, opened the patient up, and discovered a malignant cancer: poor network CAPEX management, a problem that puts telecoms in grave financial risk.  In this interview, a supplier of network analytics solutions provides greater detail on the problem and lays out its prescription for deeper asset management, capacity planning and data integrity checks.
  • History Repeats: The Big Data Revolution in Telecom Service Assurance interview with Olav Tjelflaat — The lessons of telecom software history teach that new networks and unforeseen industry developments have an uncanny knack for disrupting business plans.  A service assurance incumbent reveals its strategy for becoming a leader in the emerging network analytics and assurance market.
  • From Alarms to Analytics: The Paradigm Shift in Service Assurance interview with Kelvin Hall — In a telecom world with millions of smart devices, the service assurance solutions of yesteryear are not getting the job done.  So alarm-heavy assurance is now shifting to big data solutions that deliver visual, multi-layered, and fine-grained views of network issues.  A data architect who works at large carriers provides an inside view of the key service provider problems driving this analytics shift.
  • The Shrink-Wrapped Search Engine: Why It’s Becoming a Vital Tool in Telecom Analytics interview with Tapan Bhatt — Google invented low cost, big data computing with its distributed search engine that lives in mammoth data centers populated with thousands of commodity CPUs and disks.  Now search engine technology is available as “shrink wrapped” enterprise software.  This article explains how this new technology is solving telecom analytics problems large and small.
  • Harvesting Big Data Riches in Retailer Partnering, Actionable CEM & Network Optimization interview with Oded Ringer — In the analytics market there’s plenty of room for small solution firms to add value through a turnkey service or cloud/licensed solution.  But what about large services firms: where do they play?  In this article you’ll learn how a global services giant leverages data of different types to help telcos: monetize retail partnerships, optimize networks, and make CEM actionable.
  • Raising a Telco’s Value in the Digital Ecosystem: One Use Case at a Time interview with Jonathon Gordon — The speed of telecom innovation is forcing software vendors to radically adapt and transform their business models.  This article shows how a deep packet inspection company has  expanded into revenue generation, particularly  for mobile operators.  It offers a broad palette of value-adding use cases from video caching and parental controls to application-charging and DDoS security protection.
  • Radio Access Network Data: Why It’s Become An Immensely Useful Analytics Source interview with Neil Coleman — It’s hard to overstate the importance of Radio Access Network (RAN) analytics to a mobile operator’s business these days.  This article explains why the RAN data, which lives in the air interface between the base station and the handset --  can be used for a business benefit in network optimization and customer experience.
  • Analytics Biology: The Power of Evolving to New Data Sources and Intelligence Gathering Methods interview with Paul Morrissey — Data warehouses create great value, yet it’s now time to let loose non-traditional big data platforms that create value in countless pockets of operational efficiency that have yet to be fully explored.  This article explains why telecoms must expand their analytics horizons and bring on all sorts of new data sources and novel intelligence gathering techniques.
  • Connecting B/OSS Silos and Linking Revenue Analytics with the Customer Experience by Anssi Tauriainen — Customer experience analytics is a complex task that flexes B/OSS data to link the customer’s network experience and actions to improve it and drive greater revenue.  In this article, you’ll gain an understanding of how anayltics data needs to be managed across various customer life cycle stages and why it’s tailored for six specific user groups at the operator.
  • Meeting the OTT Video Challenge: Real-Time, Fine-Grain Bandwidth Monitoring for Cable Operators interview with Mark Trudeau — Cable operators in North America are being overwhelmed by the surge in video and audio traffic.  In this article you’ll learn how Multi Service Operators (MSOs) are now monitoring their traffic to make critical decisions to protect QoS service and monetize bandwidth.  Also featured is expert perspective on trends in: network policy; bandwidth caps; and  customer care issues.
  • LTE Analytics:  Learning New Rules in Real-Time Network Intelligence, Roaming and Customer Assurance interview with Martin Guilfoyle — LTE is telecom’s latest technology darling, and this article goes beyond the network jargon, to explain the momentous changes LTE brings.  The interview delves into the marriage of IMS, high QoS service delivery via IPX, real-time intelligence and roaming services, plus the new customer assurance hooks that LTE enables.

Related Articles

  • Telecom CVM: From Scattered Campaigns to Unified & Consistent Communication with Customers interview with Cretièn Brandsma — Despite the many failures Customer Value Management has faced in telecom, CVM’s future is very hopeful.  A carrier expert explains why telecoms have faltered, how customer experience programs can be revitalized, and where telecoms should invest in better tactics and technology.
  • The Key to Driving 4G Profit: Sell Value, Not Bandwidth by Miri Duenias — Are you struggling to earn a profit on your 4G investments?  Many operators are failing today on the marketing side.  But aligning 4G products with a customer’s personal preferences and desires provides the necessary sizzle to boost sales and earn a handsome ROI.
  • Will Real-Time Decisioning Save Big Data Analytics from Overblown Hype? interview with Tom Erskine — Telecom analytics is more than just collecting and analyzing data.  It’s also about taking action — correct action — often in real-time and across a complex provisioning environment.  In this interview you’ll hear how next best actions are creating value in retention and upselling through a more flexible, business-process driven approach.
  • A Big Data Starter Kit in the Cloud: How Smaller Operators Can Get Rolling with Advanced Analytics interview with Ryan Guthrie — Medium to small operators know “big data” is out there alright, but technical staffing and cost issues have held them back from implementing it.  This interview discusses the advantages of moving advanced analytics to the cloud where operators can get up and running faster and at lower cost.
  • The Customer Engagement Era: How Personalization & Backend Integration Leads to a Richer Mobile Biz interview with Rita Tochner — How does a mobile operator move its subscribers to higher levels of spending and profit?  Fierce competition, social media scrutiny, and the high cost of new networks all conspire against these goals.  In this interview, however, you’ll learn how engaging better with customers, getting more personal, and being more sensitive to their individual needs is the path forward.
  • Telecoms Failing Badly in CAPEX: The Desperate Need for Asset Management & Financial Visibility interview with Ashwin Chalapathy — A 2012 PwC report put the telecom industry on the operating table, opened the patient up, and discovered a malignant cancer: poor network CAPEX management, a problem that puts telecoms in grave financial risk.  In this interview, a supplier of network analytics solutions provides greater detail on the problem and lays out its prescription for deeper asset management, capacity planning and data integrity checks.
  • Batting for More Churn Reduction and Revenue Assurance Home Runs interview with Peter Mueller — What’s it like to transform an IT shop to big data and cloud?  In this interview, the CTO of a boutique revenue assurance explains how his firm made the leap.  He shows how project-oriented programs and working with carrier customers to explore RA and churn reduction “hunches” is where much of the action is.
  • History Repeats: The Big Data Revolution in Telecom Service Assurance interview with Olav Tjelflaat — The lessons of telecom software history teach that new networks and unforeseen industry developments have an uncanny knack for disrupting business plans.  A service assurance incumbent reveals its strategy for becoming a leader in the emerging network analytics and assurance market.
  • From Alarms to Analytics: The Paradigm Shift in Service Assurance interview with Kelvin Hall — In a telecom world with millions of smart devices, the service assurance solutions of yesteryear are not getting the job done.  So alarm-heavy assurance is now shifting to big data solutions that deliver visual, multi-layered, and fine-grained views of network issues.  A data architect who works at large carriers provides an inside view of the key service provider problems driving this analytics shift.
  • The Shrink-Wrapped Search Engine: Why It’s Becoming a Vital Tool in Telecom Analytics interview with Tapan Bhatt — Google invented low cost, big data computing with its distributed search engine that lives in mammoth data centers populated with thousands of commodity CPUs and disks.  Now search engine technology is available as “shrink wrapped” enterprise software.  This article explains how this new technology is solving telecom analytics problems large and small.
  • Sharing Intelligence, Services, and Infrastructure across the Telecom Galaxy interview with Gary Zimmerman — The telecom industry is an industry of sharing.  In fact, the rise of mobile broadband is driving a greater reliance on real-time intelligence, services trading, and infrastructure exchange.  In this article, a leading info exchange provider explains the value of its services portfolio and points to other interoperability and sharing ideas under development.
  • Data Monetization: Why Selling Intelligence is a Hot New Revenue Stream for Mobile Carriers interview with Joe Levy — Data monetization is a revenue dream come true for mobile carriers: a highly profitable sideshow where the carrier analyzes and sells data it already collects for other purposes.  In this article you’ll learn how operators monetize their data through use cases in corporate advertising and media branding.
  • Harvesting Big Data Riches in Retailer Partnering, Actionable CEM & Network Optimization interview with Oded Ringer — In the analytics market there’s plenty of room for small solution firms to add value through a turnkey service or cloud/licensed solution.  But what about large services firms: where do they play?  In this article you’ll learn how a global services giant leverages data of different types to help telcos: monetize retail partnerships, optimize networks, and make CEM actionable.
  • Raising a Telco’s Value in the Digital Ecosystem: One Use Case at a Time interview with Jonathon Gordon — The speed of telecom innovation is forcing software vendors to radically adapt and transform their business models.  This article shows how a deep packet inspection company has  expanded into revenue generation, particularly  for mobile operators.  It offers a broad palette of value-adding use cases from video caching and parental controls to application-charging and DDoS security protection.
  • Radio Access Network Data: Why It’s Become An Immensely Useful Analytics Source interview with Neil Coleman — It’s hard to overstate the importance of Radio Access Network (RAN) analytics to a mobile operator’s business these days.  This article explains why the RAN data, which lives in the air interface between the base station and the handset --  can be used for a business benefit in network optimization and customer experience.
  • Back Office Streamlining to Enterprise Support: The Many Flavors of Wireline Analytics interview with Tom Nolting — Mobile analytics gets plenty of press coverage, but analytics is just as crucial for wireline operators.  In this article, a billing VP at a leading wireline operator discusses several diverse uses of analytics in billing, enterprise sales/retention, and network partner margin assurance.
  • Analytics Biology: The Power of Evolving to New Data Sources and Intelligence Gathering Methods interview with Paul Morrissey — Data warehouses create great value, yet it’s now time to let loose non-traditional big data platforms that create value in countless pockets of operational efficiency that have yet to be fully explored.  This article explains why telecoms must expand their analytics horizons and bring on all sorts of new data sources and novel intelligence gathering techniques.
  • B/OSS Mathematics: The Quest to Analyze Business Problems & Drive Operating Decisions interview with Matti Aksela — Analytics is the glory of mathematics brought to practical use.  And in telecom, analytics has merely stratched the surface of its full potential.  In this article, you’ll learn how machine learning is being combined with the power of CDR number crunching to optimize mobile top-ups, control churn — and in the future, help telecoms make critical network and operating decisions.
  • Leveraging the RA/FM Platform to Deliver Business Insights to Finance & Marketing by Amit Daniel — Carrier professionals using RA and fraud management tools are getting requests from internal customers who want the role of RA/FM platforms expanded to deliver up-to-date analytics data for finance and marketing purposes.  This article advocates a cross-product layer to serve such broader use cases.  The effect would be to transform the existing RA/FM platform into a combined business protection and business growth analytics engine.
  • A Mobile Marketer Service: Bridging Personalization & B/OSS Flowthrough interview with Efrat Nakibly — Marketing analytics is a prescriptive program for driving  actions such as sending a timely promotion to a mobile subscriber.  But completeness demands that you also be able to provision that treatment, qualify the promotion, and keep billing fully in the loop.  This article shows how a managed services program can deliver such an end-to-end process and manage customer life cycles on a one-to-one basis.
  • Science of Analytics: Bringing Prepaid Top Ups & Revenue Maximization under the Microscope interview with Derek Edwards — Prepaid subscribers are the customers that carriers know the least about.  The operator is not interacting with prepaid customers on a monthly basis.  You’re not sending a bill, nor do you have detailed profiles on these customers, especially in the developing world where customers are buying SIMs at a grocery store.  This interview explains how contextual marketing meets the unique analytics challenge of prepaid customers.
  • Connecting B/OSS Silos and Linking Revenue Analytics with the Customer Experience by Anssi Tauriainen — Customer experience analytics is a complex task that flexes B/OSS data to link the customer’s network experience and actions to improve it and drive greater revenue.  In this article, you’ll gain an understanding of how anayltics data needs to be managed across various customer life cycle stages and why it’s tailored for six specific user groups at the operator.
  • Profitable 3G: China’s Mobile Operators Monetize Networks with Retailers & Partners interview with Kevin Xu — Mobile operators are at the center of explosive growth in wireless services.  But to exploit this opportunity requires IT ingenuity and a broader view on how the mobile user can be served.  In this article you’ll learn the innovative techniques Chinese operators use to monetize 3G networks via analytics and partnerships with retailers, social networks, and advertisers.
  • Customer Analytics: Making the Strategic Leap From Hindsight to Foresight interview with Frank Bernhard — Are your company’s analytics programs scattered?  Is there a strategy in place for customer analytics?  This interview with a leading telecom analytics consultant explains why strategy and planning around the analytics function is crucial to getting your money’s worth.  Topics discussed include: hindsight vs. foresight; an advanced analytics program; and the interface sophistication required to support high end vs. low end analytics users.
  • Meeting the OTT Video Challenge: Real-Time, Fine-Grain Bandwidth Monitoring for Cable Operators interview with Mark Trudeau — Cable operators in North America are being overwhelmed by the surge in video and audio traffic.  In this article you’ll learn how Multi Service Operators (MSOs) are now monitoring their traffic to make critical decisions to protect QoS service and monetize bandwidth.  Also featured is expert perspective on trends in: network policy; bandwidth caps; and  customer care issues.
  • Analytics Meditations: The Power of Low-Cost Hardware and the Social Network Within interview with Ken King — Analytics didn‘t arrive yesterday.  Data warehousing and BI have been in the telecom vocabulary for twenty-five or more years.  In this interview, you’ll gain a perspective on why “big data” changes the game and why social network (or social circles) analysis promises the next level of insights.  Other interesting topics include: segmenting the analytics market, engaging with carrier clients, and upgrading from older- to newer-style methodologies.
  • LTE Analytics:  Learning New Rules in Real-Time Network Intelligence, Roaming and Customer Assurance interview with Martin Guilfoyle — LTE is telecom’s latest technology darling, and this article goes beyond the network jargon, to explain the momentous changes LTE brings.  The interview delves into the marriage of IMS, high QoS service delivery via IPX, real-time intelligence and roaming services, plus the new customer assurance hooks that LTE enables.
  • Shared Data Plans: The Challenge of Managing a Family of Pricing, Revenue Assurance, Fraud, and Network Policy Issues by Amit Daniel — Verizon Wireless‘ recent announcement of its move to shared data plans for families shook the mobile industry.  In this column, cVidya’s Amit Daniel shines a spotlight on the knowhow and analytics tools that operators now deperately need to offer the right  shared data price plans, ensure bandwidth throttling is handled correctly, and address new fraud concerns.
  • Analytics Guru: Are Telecoms Ready for the Biz Intelligence Explosion? interview with John Meyers — Business intelligence is evolving from the creation of dashboards and reports to taking action based on a deep knowledge of the environmental context.  The article explores the implications of “big data” in terms of IPTV, storage requirements, hardware, event collection, and deep packet inspection.
  • Social Networking for Telecoms: How To Enlist Friends and Family as Mobile Marketers interview with Simon Rees — Social Network Analysis (SNA) is about exploiting data on “friends and family” connections to combat churn and win new CSP business.  The article explores how an analysis of the ebb and flow of CDRs, phone calls, and messages, can identify key influencers and drive powerful marketing campaigns.
  • Making the Strategic Leap From Billing to Merchandising interview with Humera Malik — Today billing/charging technology has progressed to the point where the usage intelligence, the charges, the user behaviors, and the analytics can all come together in near real-time.  This article discusses the organizational and marketing strategies that enable a operator to create a true “merchandising” system that can revolutionize a CSP’s business.