This document summarizes research on self-optimization apps that track personal data ("Me Data"). Key findings include: - Users are largely unconcerned with data privacy and willing to share data publicly in exchange for benefits like performance tracking and visualization. - Motivation for using these apps is mainly self-improvement through goals like better organization, knowledge, and behavior changes. - Emerging opportunities exist for innovation in apps that optimize new lifestyle areas like productivity, travel, shopping and leisure using personal data. - Developers should focus on effectively analyzing, storing and visualizing personal data as well as ensuring intuitive user interfaces and accurate, easy-to-use data collection.

1. ME DAta
The Rising Opportunity for Self Optimization Apps
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2. The Rising Opportunity for ‘Self Optimization’ Apps
Beyond’s new research study, The Me Data Opportunity for Self Optimization Apps, demonstrates a growing
opportunity for new Self Optimization apps and services. This has been created in response to the growing
trend in the creation of social Me Data -­ open, freely available, personal data -­ and people’s radically changing
attitudes to privacy and sharing when using Personal Tracker services such as Nike+, Mint, Evernote and Fitbit.
Me Data
Research Highlights
The research report -­ conducted in Q4 2012 and based on a comprehensive analysis of global social media conversations surrounding Personal Tracker apps, a category
that has grown by 155% from 2011 to 2012 -­ reveals the following:
1. 2. 3. 4.
Data Privacy Public Sharing Self Improvement Innovation
Data privacy is a basically a non-­concern Public social sharing of data -­ an intrinsic This app category is overwhelmingly The main market categories
among Personal Tracker app users and function of all of Personal Tracker apps associated with self-­improvement. Of for Personal Tracker apps are
those talking about them. Less than 2% those conversations related to app
of all conversations about Personal milestones and health information, usage, 22% are concerned with productivity/organization. But their
Tracker services are related to this keeping record of web and social media acquiring self-­knowledge, 33% are growth points to further opportunities
aspect of the apps. This suggests that content and the generation of personal concerned with better organization for innovation by brands and startups
people who use services like Nike+ and lists) -­ is also a low concern. Only 8% of and 45% are concerned with changes looking to create new kinds of Me
Evernote are happy to generate a mass all conversations about the apps are in personal behavior. This suggests that Data, via new tracker services. These
related to this theme. This suggests motivation for app usage is mainly driven would aim to help people improve
based on that data, such as performance that users are equally happy to share by the basic desire for change -­ which is their daily lives across multiple
tracking, data visualisations, and data their Me Data on social media platforms particularly relevant at the turn of the new different Lifestyle Optimization
storage and accessibility. in return for associated community year as people look to set new goals and categories, such as personal
resolutions. (We fully expect a peak in the productivity, travel, shopping and
regimes among friends, or public sharing generation of Me Data via these apps -­ leisure.
of web content around common interest and social conversations about them -­ in
categories. January.)
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3. Research Summary Conclusions
In conclusion, this new study Taken as a new trend, this rise of Me Data points to a
highlights some radical changes “...users are very willing to
in people’s attitudes to data Optimization applications in new lifestyle categories. overlook traditional privacy and
privacy and sharing of personal
sharing boundaries in exchange
If the value proposition is right -­ if brands and startups
types of Personal Tracker apps. It can pinpoint the most compelling reasons for the
appears that users are very willing creation, tracking, visualizing and cross-­fertilisation brought by apps such as Nike+.”
to overlook traditional privacy and of personal data -­ then we can expect to see a rise in
sharing boundaries in exchange for the data-­driven new kinds of Self Optimization apps in new categories.
These include: personal productivity (helping workers to
optimize the time they spend on productive work);; travel
(helping people to optimize the time and cost of their
The net effect of this open approach to data and sharing regular travel patterns);; shopping (helping customers to
is the creation of a new and rapidly growing subset of reduce the cost of their regular purchases);; and leisure
data, which is now freely accessible in the public domain. (helping people to optimize the use of their day-­to-­day
We’ve coined this growing data set Me Data, which leisure time).
one can view as a very
personal and human “Me Data enables companies This development trend is already
component of today’s Big
to tap into some key behavioral taking shape. For example, in
Data trend. December 2012, Nike announced its
consumer insights, based new Nike+ ‘Accelerator’ program, in
At the same time, the extrapolation of Me Data from Big
Data in the social domain provides great opportunity for
The creation of Me Data upon concrete desires for self product and brand planners. Me Data enables companies
(open, freely available, TechStars, which aims to identify,
improvement.” to tap into some key behavioral consumer insights, based
personal) appears to be help and fund third party developers
upon concrete desires for self improvement. An analysis of
happily driven by a very that are interested in leveraging Nike+
consumer sharing habits and conversational trends around
concrete impulse: the desire to improve oneself (in return technology and data to create new applications and
these new application areas should bring new depths of
for the free exchange of one’s personal data). service models based upon Nike+ API and SDK. (For
insight for future product and service development.
further information, see here.)
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4. Guidance For Personal Tracker App Developers
The study highlights the following key focus areas for developers of Personal Tracker apps:
App Features App Functionality
56% of all conversations are concerned with 18% of conversations are concerned with the quality of
the apps’ ability to analyze and store personal the apps’ user interfaces and general user experiences. A
56% data effectively. Features such as rich, time-­based 18% good UI is a clear point of differentiation among apps.
performance visualizations and personal graphing
are compelling.
18% of conversations are concerned with the ease of
8% of conversations are concerned with an app’s
18% data entry. Users need data recording to be quick, easy
and intuitive.
8% across multiple devices -­
from laptops to tablets to smartphones.
14% of conversations are concerned with accuracy of
14% data measurement. This is in conjunction with application
run tracking. Obviously, better quality data means a better
user experience and better app value.
Me Data
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5. Research Background ABout Beyond
Creative digital agency Beyond is part of the Next 15 group of companies. Since its formation in August 2010,
research in four phases. First, it conducted exploratory research Beyond has grown rapidly off the back of its deep social data analytics and digital creative capabilities to
to identify what kinds of Personal Tracker conversations existed
online. The six Personal Tracker apps in the marketplace that
were most frequently mentioned were Nike+, MyFitnessPal, Mint.
com, Fitbit, Cozi and Evernote.
Beyond’s Insight and Analytics team are experts at mining social data using a combination of technology and
Second, Beyond developed comprehensive semantic strings human analysts to work with brands such as Visa, Virgin, 3, Sprint, Cisco to develop both product and customer
that targeted the kinds of highly-­relevant content uncovered insights, content and digital strategies, as well as measure the impact of campaigns online. More about our
in exploratory research, and ran them against its social media approach can be found here.
databases. Third, Beyond took the content uncovered by its
searches and executed an in-­depth analysis and categorization
of it using human analysts. Lastly, Beyond used the resulting
Further Information
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insights into usage of Personal Tracker products.
bynd.com For further information about this release, Twitter: @beyond
please contact: marketing@bynd.com Facebook: facebook.com/beyondconsultancy
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