Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice

Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
Data Monetization in
the Age of Big Data
By Astrid Bohé, Montgomery Hong,
Craig Macdonald and Nigel Paice
Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
Harnessing the potential of Big Data seems to be on the
agenda of every mobile operator—and rightly so. In today’s
climate of convergence, in which new technologies and
networks are blurring industry lines, the mobile phone
has become the hub of insight into consumer behavior.

The volume and richness of the     Not surprisingly, operators        How can mobile operators best
data now uniquely accessible       today are talking about when       approach this new territory?
to mobile providers—whether        and how to tap into this data      What are the opportunities
in the form of transactions,       and what to do with it. In         and challenges? And how can
inquiries, text messages or        particular, they want to know      operators shape new business
tweets, GPS locations or live      how to monetize it: how to         models to monetize their
video feeds—offers a veritable     sort, analyze and manipulate       Big Data?
gold mine of insights and          the data and put it to use. This
applications. And even as          holds true not only for internal
mobile phones have become          applications, but increasingly
the primary device through         for building new revenue
which consumers get their          streams or collaborating on
information, those very same       external applications with
devices have begun to facilitate   third parties as well.
new types of information,
including extremely precise,
real-time, geolocation
                                                                            Data Monetization in the Age of Big Data 1
Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
2 Data Monetization in the Age of Big Data
Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
The Data Opportunity

Analyzing and employing customer data          FIGURE 1. A Number of Forces Are Converging to Create Conditions Ripe for Data Monetization
is nothing new. Traditional sources of         Source: Accenture analysis
data have been used to improve sales
and marketing performance since the first
mail-order catalog was produced and
                                                              Daily volumes massively increasing
distributed more than two centuries ago.
From monthly sales reports to predictive
                                                                        Cost of data storage massively decreasing
business intelligence, tapping into
customer data is a well-known way
                                               Business Intelligence and Analytics top of C-suite agendas
to enhance efficiency, build customer                                                                                                   Monetization
relationships and generate new revenues.            Emerging technologies enable real-time execution

In recent years, however, the nature                                        Increasing value of Big Data and Analytics
of the data environment has changed.
Digital technologies now enable massive                 Recognition of amount of under-utilized data
data collection, as the cost of data
storage has fallen. Other technology
advances facilitate real-time data
analysis and personalized communication.       This location-specific data is unique to                    Internal opportunities
Simultaneously, there has been a               the mobile world and invaluable to both
realization that an enormous amount            operators and their customers. It allows                    Mobile operators have a number of
of the data being produced could offer         operators to enhance their internal systems,                opportunities to utilize their unique
additional value if enhanced and analyzed      drive loyalty programs and stem attrition.                  data sets. Looking internally, a range of
to tap its potential (see Figure 1).           Their mobile customers, in turn, can receive                marketing, customer service and network
                                               location-specific data such as restaurants                  management applications are available
Mobile operator advantages                     and events in their area, enhanced with                     before mobile operators even begin to
                                               behavioral- and location-targeted                           derive new revenue streams from third-
Mobile operators have many advantages as
                                               advertising and information services.                       party businesses. Just looking at customer
they approach this changing data market.
                                               And there is no more popular smartphone                     activity across the mobile network in a
They have the advantage of customer
                                               application than maps.                                      more analytical way, for example, can
micro-segmentation data and other
                                                                                                           improve a mobile operator’s infrastructure
valuable customer information about
                                                                                                           management and save costs across
application and mobile website usage.
                                                                                                           the organization. In addition, Big Data
And in particular, they have the advantage
                                                                                                           technology and analytics can build cross-
of data sets that are very specific to the
                                                                                                           sell and up-sell efforts, enhance internal
mobile industry, as technologies allow
                                                                                                           network management, and support
them to pinpoint the real-world geographic
                                                                                                           customer service in general.
location of millions of active mobile users—
whether through GPS, Wi-Fi hot-spot usage
or network caller-data records (CDRs).

                                                                                                                         Data Monetization in the Age of Big Data 3
Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
FIGURE 2. Data Value Continuum: Driving Value from Raw Data to Insights
Copyright © 2013 Accenture. All rights reserved.

What’s done at each stage

• Data-driven interactions with end-users                                                                                             VALUE OF DATA
• APIs and ability for companies to access
  platform and data                                                           TRANSACT

• Applications that present insight in intelligible formats
• Business intelligence and performance management software                 PRESENTATION
• Enable improved decision making

• Data science, data mining, predictive
  modeling, analytics                                                          INSIGHTS

• Secure capture and transport of data
• Data processed in a summary form
• Storage and management of data
                                                                           PROCESSED DATA
• Platform

• Raw data from a source not yet
  processed                                                                   RAW DATA

                                                                                                                                     VOLUME OF DATA

External value                                                Of course, being a pure data provider is a    In addition, Precision Market Insights from
                                                              relatively low-value option, minimizing the   Verizon generates analytics-driven behavioral
Looking externally, mobile operators can                      opportunity to provide enhanced services.     insights based on mobile engagement,
add value to a range of other industries,                                                                   location and demographics information,
including retail, advertising, marketing, the                 Moving up the pyramid as data is further      creating a 360-degree view of the consumer.
public sector, financial services, healthcare                 processed, operators begin to create          For outdoor advertisers, for example, such
and other customer-facing businesses.                         applications and insight products that        insights can measure the effectiveness of
                                                              sit on top of the data. These offerings       outdoor advertising units, validating the
The wealth of external opportunities                          help generate new value-added services        impact and reach of specific ad campaigns.
is illustrated through the data pyramid                       and create platforms for data-driven
(see Figure 2), which overlays the stages                     transactions such as ad targeting, retail     At the top of the pyramid, mobile operators
of data processing and types of output                        payments and the provision of customer        create platforms on which customers
(orange) onto the value that data creates                     insights. The recent launch of Telefónica     become part of a transactional ecosystem.
(yellow). At the bottom of the chart, mobile                  Dynamic Insights is a good example; this      02’s Priority Moments application, for
operators can, if they choose, sell only                      service collects and aggregates anonymous     example, provides tailored, exclusive offers
the raw data they have in hand. A good                        customer data in real time to understand      to its mobile customers based on detailed
example is the collaboration of Ford Motor                    how segments of the population behave as      data provided with the customer’s consent.
Company with INRIX, a leading provider                        a group, thereby helping local governments
of traffic and navigation services, which                     and businesses make better decisions. A       Mobile operators may choose where to play
now provides Ford with real-time traffic                      retailer thinking of opening a new store,     in the value pyramid. To determine the
information and enhanced routing for all                      for example, can see how many customers       appropriate approach, they should make
Ford vehicles with Ford SYNC, an in-car                       visit a given location each day by time,      a careful assessment of the local market,
communications and entertainment                              gender and age.                               the opportunities, the legal and regulatory
system developed by Ford and using                                                                          challenges and their own capabilities.
Microsoft technology.                                                                                       There are no off-the shelf solutions, and
                                                                                                            opportunities will vary widely.

4 Data Monetization in the Age of Big Data
Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
The Data Challenge
The new opportunities to monetize data are as vast
as Big Data itself, and no doubt many are still to be
identified. Companies such as mobile operators—which
sit on large amounts of customer data—have a unique
opportunity: With their direct relationships with
customers, they are likely to have the most accurate
and complete customer information, unlike third-
party information providers that must rely on publicly
available or purchased customer information.1 Yet
mobile operators still may hesitate to enter the arena
for any number of reasons. They may be risk-averse,
believing they lack the knowledge, resources or skills to
go it alone or the scale to make Big-Data applications
worthwhile. They may have privacy concerns as well.

As they approach the data monetization opportunity,
therefore, mobile operators will need to ask themselves
a number of important questions. Where do they
want to play strategically in the value pyramid?
What products and services would they like to offer
and develop? Do they have the appropriate skills and
resources in-house? Do they have the appropriate data
in the relevant form for the end user? What are the
technology options available and which are the most
relevant? How will they go to market and what will
the roadmap look like to achieving their objectives?

1. Accenture, “How Big Data can fuel bigger growth,” Sumit Banerjee, John D. Bolze,
James M. McNamara and Kathleen T. O’Reilly, October 2011,

                                                                                            Data Monetization in the Age of Big Data 5
Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
Getting Started
Determine a strategy                             Teaming with other organizations and           should also be separate, dedicated
                                                 third-party data providers will help enhance   infrastructure to support the data
To resolve these issues, players must begin      an operator’s offerings and smooth the         monetization business, as there will be a
by agreeing on the opportunity, and by           route to market.                               requirement in the first 18 to 24 months
defining clear objectives and a strategy,                                                       for quick scalability and flexibility, given
as success will not only be about setting        As with any strategic project, negotiating     the need for agility in the product and
up the appropriate IT solutions or analytics     with allies is complex. However, such          go-to-market processes. Service or outage
software. They must then identify the            alliances are often critical to bridging the   failures in the beginning of the service
appropriate collaborators and define             data gap. Retailers and banks, for example,    delivery could harm customer confidence
the plan to mobilize for action. Figure 3        may provide additional data around             and should be avoided.
outlines the key steps that mobile               demographics, household details,
operators should take when launching             transactions and product consumption           In addition, investments should be made
a data monetization business.                    that can be packaged with wireless data        to ensure continuous development and
                                                 to make it more valuable to third parties.     improvement of the data and of the
Once operators understand where they                                                            algorithms used to translate the raw data
want to play in the data market, they
                                                 Operational excellence                         from the mobile provider into useful data
should consider seizing first-mover                                                             for the supported applications.
advantage. Despite the potential risks,          Choosing appropriate collaborators will help
the market is changing rapidly and               mobile operators gain the scale they need
operators need to move quickly. With many        to move products and applications from
applications there may only be room for one      concept to market rapidly, whether through     Data insights must be combined with a
or two players in a given application area;      additional subscriber coverage, added          proactive privacy policy that both protects
sitting back and waiting to see what others      resources and skills, or IT infrastructure.    customers and convinces them it is in their
will do may mean missed opportunities.           Operators should also acquire talent from      best interest to share their data. Mobile
                                                 the marketplace, teaming key internal          operators are often afraid to move into the
Operators can mitigate the potential risks       entrepreneurs with new staff.                  data monetization arena due to privacy
by testing the waters with small, cloud-                                                        issues, fearing they will compromise the
based proofs of concept, using lean and          Most teams will start small, building up the   customer experience or lose customer trust.
agile analytics and product design and           new platforms as they begin to prove their     To prevent this, operators should ensure
trialing the use of various solutions without    value. Nonetheless, the eventual scale of      they have the security and encryption
the need to invest enormous amounts in           business and IT operations required for        necessary to protect their customers’ data,
internal platforms and systems. These            successful data monetization should not be     based on the standards and laws of each
cloud-based solutions can be scaled quickly      underestimated, as multiple products based     individual country in which the operator
and flexibly and turned off quickly if need      on the same underlying data are typically      conducts business, allowing them to feel
be. In addition, relying initially on external   needed to realize sufficient revenues to       totally confident that customer security
resources and suppliers would provide            support a data monetization business.          cannot be compromised.
flexibility and speed, allowing mobile
operators to access and manage resources         Separate and scalable                          Operators should make the customer
and skills appropriately and efficiently as                                                     experience the driver for enhancing
                                                 infrastructure                                 permissions and privacy. Most importantly,
requirements change.
                                                 Operators will need to establish a robust      customers should be able to choose the
Collaboration                                    technology infrastructure to manage            ways in which their data can be used by the
                                                 the sheer velocity, volume, variety and        mobile operator—opting in or out according
Mobile operators should look for allies to       complexity of Big Data—whether on              to their preferences. In addition, creating
support them in these new business models.       their own or through an infrastructure         transparency around data sharing can allow
Data applications cut across many different      outsourcing partner. While internal            customers to know how their information
industries, requiring a breadth of knowledge     technical platforms and standards can and      is being used and applied, secure that their
to understand all the ways in which data         should be used to leverage the purchasing      personal details remain with the operator
can be applied and marketed in each area.        power of the parent organization, there        and are not being re-sold to other

6 Data Monetization in the Age of Big Data
Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
FIGURE 3. Five Steps to Launching a Data Monetization Business
Copyright © 2013 Accenture. All rights reserved.

             STRATEGY                      PLAN                  MOBILIZE              DELIVER                  LAUNCH

             • Data assessment             • Roadmap and         • Data sourcing and   • Data refining          • Brand and PR
             • Products and                  program plan          transformation
                                                                                       • Data science           • Marketing
               target industries           • Program             • Anonymization         analysis, insights       materials and
             • Partners (sales,              governance and        and privacy           and innovations          launch plan
               platform, data,               PMO                 • Platform setup      • Visualization and      • Customer service

               collaboration)              • Architecture        • Operating model       transact                 and technical
             • Business plan               • Pricing             • Sales operations      applications             support
               and high-level              •    Business case      and pipeline        • Customer and
               business case                                     • Innovation and        user testing and
             • Technology                                          product roadmap       feedback

             •   Options selected           • Capex investment   • Technology          •   Product socialized   •   Business and
                 for product,                 justified            infrastructure          with customers           product launched

                 industry verticals,        • Program start-up     setup                   and ready for            to marketplace
                 partners,                    mobilized          • Business                launch
                 collaboration,                                    operations
                 technology                                        initiated

                                                                                                                     Data Monetization in the Age of Big Data 7
Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
Final Thought

Mobile operators need not be overwhelmed by Big Data, even in today’s
competitive and converging business environment. Instead, they should look
inward to assess their company’s priorities and the options available, then
look outward to identify market opportunities and find the support required
to scale up their offerings as needed. One mobile operator overcame its
initial reluctance, carefully assessed the opportunities and challenges, and
went on to build and launch a new insight product in just nine months,
with projected revenues of $200 million over two years. This is likely to be
just the start, as the operator is developing new applications for a wide
range of industries.

8 Data Monetization in the Age of Big Data
About the Authors                                          About Accenture Analytics                          About Accenture
Montgomery (Monte) Hong is                                 Accenture Analytics delivers insight-driven        Accenture is a global management
Accenture’s global Communications                          outcomes at scale to help organizations            consulting, technology services and out-
Industry practice lead and the global                      improve performance. Our extensive                 sourcing company, with approximately
Accenture Customer Operations Services                     capabilities range from accessing                  266,000 people serving clients in
lead.                                                      and reporting on data to advanced                  more than 120 countries. Combining
                                                           mathematical modeling, forecasting and             unparalleled experience, comprehensive
Astrid Bohé is the Global Accenture
                                                           sophisticated statistical analysis. We draw        capabilities across all industries and
Analytics lead for the Communications,
                                                           on over 16,000 analytics professionals             business functions, and extensive research
Media and Technology practice.
                                                           with deep functional, business process             on the world’s most successful companies,
Craig Macdonald is the global capability                   and technical experience to develop                Accenture collaborates with clients to
lead for Data Monetization within                          innovative consulting and outsourcing              help them become high-performance
Accenture Interactive.                                     services for our clients in the health,            businesses and governments. The company
                                                           public service and private sectors. For            generated net revenues of US$27.9 billion
Nigel Paice is the Accenture Interactive
                                                           more information about Accenture                   for the fiscal year ended Aug. 31, 2012.
lead within Europe for Customer Analytics
                                                           Analytics and our journey to analytics             Its home page is
and Data Monetization.
                                                           ROI, visit

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