Mobext Point of Viev form Mobile World Congress 2015

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ADRIAN KIELICH, HEAD OF MOBEXT, GERMANY
FROM BIG DATA TO SMART DATA
This year, the Mobile World Congress expects more than 90,000 people, from
more than 160 countries and international organizations. There are nearly
2,000 exhibitors over 100,000 square meters of exhibition and hospitality
space. Each year at the MWC we have the opportunity to see and test a myriad
of new devices, wearables and other appliances with built-in sensors. And they
all produce an enormous amount of data.
DATA OVERLOAD?
Already each day, we generate 2.5 trillion bytes of data. 90% of the data
existing in the world has been created during the past 2 years. This data
comes from everywhere: posts on social media networks, pictures and videos
posted online, transactional records of online shopping, GPS signals of mobile
phones…
The development of connected objects is expected to increase the volume of
available data and strengthen the challenges of data collections for many
companies. Indeed, a report called “The impact of the Internet of Things”
released yesterday by GSMA Intelligence and KRC Research, shows that
approximately 25% of people in Germany, Japan, the UK and the US already a
connected device! In addition, 89 percent of all research respondents
confirmed that they could like all of their household devices to be
seamlessly connected together in the future.
“Advocates” of privacy express concerns about
the overload of data…and some will try to
control it.
Silent Circle launched the super secure
Blackphone 2 smartphone and tablet. It goes
against the concept of Big Data. The brand
promises a host of security and privacy-centric
features. Users also benefit from anonymous
searching, encrypted phone calls and private
cloud storage. It is expected to retail for
approximately USD $629.
DATA AND BUSINESS
We all know data can help us understand consumers and their needs. We use
that insight to create better mobile experiences that will affect our business.
However, data is also a huge business on its own.
Image : Engadget

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“I see revenue in (connected)
garbage cans,” Ralph de la Vega,
AT&T Mobility & Business
Solutions, President & CEO
In an interview released during the MWC to Business Insider yesterday, Chris
Moody, VP of Data Strategy at Twitter talked about how Twitter is making
money with data. Twitter now licenses its data through subscriptions,
targeting business software providers like Oracle, Salesforce, and IBM as well as
advertisers (new revenue streams). Twitter has launched a “syndicated”
strategy to increase data mining, working with partners such as Flipboard and
Yahoo. Finally, they also partnered with IBM to provide Twitter data within
IBM’s business decision making dashboards. This step allows businesses to
deliver good customer service through learnings from social media.
While the example of Twitter is about social, we know that mobile data, in
particular, will become more important as it allows us to gain far deeper
real-world insights.
Marketers, like us, will need to manage massive amounts of data, from more
and more sources (smart meters, lighting, cars, health monitors, washing
machines, smart watches, activity trackers, ovens, refrigerators and elderly
monitors…) collected through more and more sophisticated analytics solutions
(mobile specific analytics, DSPs etc..). How can we smartly use data in our
business?
OUR INSIGHT
‘Mobile-first’ DMPs will help us build up a deeper, enriched picture of audiences
that can be targeted at scale or enable true personalization of mobile
experience, as they will connect data and business seamlessly; this is where we
must focus our attention. These tools are ready for digital but not yet fully-
adapted to mobile.
How can we be strategic with data? How can we drive data and channel it?
How can we lead data, shape data and make data perform to match our
business strategies?
We have to define our business purpose, and create the mobile experiences
that will deliver the data we require. Rather than just using the data we have,
we must actively develop the data we need.
It’s not the objects, applications or technology that must be smart. It’s how
we approach data from the very beginning that needs to be smart.