Data Monetization in the Age of Big Data - By Astrid Bohé, Montgomery Hong, Craig Macdonald and Nigel Paice
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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
information.
Data Monetization in the Age of Big Data 1
2 Data Monetization in the Age of Big Data
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
Data
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
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
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, http://www.accenture.com/us-en/
outlook/Pages/outlook-journal-2011-how-big-data-fuels-bigger-growth.aspx.
Data Monetization in the Age of Big Data 5
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
Privacy
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
businesses.
6 Data Monetization in the Age of Big Data
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
ACTIVITY
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
blueprint
• Options selected • Capex investment • Technology • Product socialized • Business and
for product, justified infrastructure with customers product launched
OUTCOME
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
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 www.accenture.com.
and Data Monetization.
ROI, visit www.accenture.com/analytics.
Contact Us About Accenture Interactive
Please visit www.accenture.com/customer-
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visit accenture.com/interactive.
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