Mobile network data is a unique and valuable asset for mobile operators. By analyzing network data and combining it with external data sources, operators can gain deep insights into consumer behavior and network performance. This allows operators to better understand individual consumers, identify new business opportunities through partnerships, and improve network efficiency. The prototype data analysis tool presented demonstrates how network data can be made understandable through visualization and interaction. It highlights the potential for increased consumer loyalty and new revenue streams from leveraging the power of big data. However, consumer awareness and concerns regarding privacy must be addressed through transparency, perceived value of any data sharing, and only utilizing anonymized and aggregated information.

1. Exploring Big Data
Mobile World Congress 2013

2. In a nutshell
› Mobile network data as an asset
– Mobile network data is an unique asset that the operators have – if treated the right way.
In this project we provide a prototype tool that demonstrates how this can be achieved.
› Deepened consumer understanding
– Historically, consumer segmenting has been used in order to understand the market, but
going forward, it will become vital to understand the individual also through Big Data, to build
a stronger relationship with the consumer leading to improved consumer experience & loyalty
› Data insight driven business innovation
– By connecting, mining, and analyzing vast amount of data sources (coming from mobile
networks as well as external sources) in a Networked Society, without jeopardizing consumer
needs for privacy and integrity, Ericsson can provide insights that enable the identification
and creation of new business opportunities. This is exemplified in the prototype tool.
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3. Understanding mobile
network data
› Extremely “rich” data
– Mobile network data can contain a plentitude of various
parameters, such as network traffic load, types of
communication, and content being consumed, etc.
› Presentation of data is key
– In order to be able to understand network data it has to
be visualized and made possible to interact with.
› Analyzing network data – and merging it with other
data sources
– By combining mobile network data insights with external
data sources, a broad and deep comprehensive analysis
can be achieved.
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4. Consumer Understanding
› Consumer awareness is increasing, but still
limited
– Many consumers are aware that their data is PERMISSIBILITY
collected, but not why, how or exactly what
› Benefits beats sensitivity
– If the consumer can see a clear and wanted benefit
they also become less concerned VALUE SHARING
› Permissibility, value sharing & transparency
are key!
– Permissibility and transparency will increase
consumer trust and mutual value sharing is a profit TRANSPARENCY
driver and gives consumer “free” or better services
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5. Data insight driven
business innovation
› Data and information that are unique to the
operator – strong assets
– Difficult for other players such as Google and Apple to get
hold of this kind of data – a differentiating factor for the
telco players.
› Leveraging on data analysis insights
– Partnerships around network data “products”
– Improved network performance and potential increased
network traffic (related to learning and prediction
mechanisms)
– Deeper customer understanding
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6. DATA ANALYSIS TOOL
(PROTOTYPE)
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7. Data Analysis Tool (Prototype)
› Makes network data understandable
– In order to be able to understand network data it has to be
analyzed, visualized, and made possible to interact with.
› Illustrates network performance and behavior
– Shows possibilities for increasing efficiency dynamically
(as a result of network data analysis and prediction
mechanisms), and more.
› Highlights new business opportunities and
innovation
– Network data analysis is an valuable asset.
– Shows the potential in forming new kinds of partnerships.
– Allows for increased customer loyalty through deeper
consumer understanding (thus reducing churn).
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8. Consumer Research material
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9. Consumer Research material
› Qualitative research in San Francisco, US
› 6 in-depth interviews
› 7 expert interviews
› Explorative workshop with 16 university students
› Fieldwork: 30 October 2012 -14 January 2013
› Quantitative research in 15 markets
› 23 000 online interviews
› Age 15-69
› Representing more than 630 million consumers
› Fieldwork: May 2012
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10. Anonymous data not
considered sensitive
When personal information is collected and aggregated on a large scale
Value & by companies, privacy and integrity risks arise. What do consumers think
Sensitivity about collection of aggregated, anonymized information?
› Although consumers have a very low awareness of CONSUMERS ARE UNCONCERNED BY THE
companies’ and organizations’ use of aggregated, RISKS OF USE OF AGGREGATED DATA
anonymized personal information, it is not seen as
particularly sensitive.
› Consumers are more willing to accept the collection
My personal information might be useful,
and use of their aggregated information by a company say if 75% of the people in my demographics
to which they have an existing relationship. actually liked a TV show, maybe I should
check it out., and I don’t have to spend time
› For companies with a long standing relationship to the reading reviews.
consumer, some will even accept the fact that their
aggregated personal information could be sold to a third party Beth, 46, consumer
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11. Consumer Awareness of companies
collection of pi
More than 50% people think that mobile phone providers and social
networking sites use their personal information for commercial purpose
Source: Infocom Advance 2012 Base: Internet users
Q: To what extent do you think the following organizations use your personal information for commercial purposes (e.g. advertising, monitoring)?
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12. Personalization is value
More than 40% people would allow companies to use their personal information when
offer is personalized to them, used to improve current services or develop new services
Source: Infocom Advance 2012
Base: Internet users
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