Improving the listening experience through context-aware discovery. (July 2013) - Download the 'Putting Music in Context' whitepaper for free at http://www.arguslabs.be

1. PUTTING MUSIC
IN CONTEXT
Improving the listening experience through
context-aware discovery.
JULY 2013
www.arguslabs.be
by R. Berger, D. Damen, K. Underseth and A. Wuyts

2. TABLE OF CONTENTS
Introduction to context 3
Introduction to Argus Labs 4
Real-world applications 5
Applying context - data flow 6
Benefits of a contextualized user experience 8
For individuals
For music services
Technical Integration 9
Contextualization Platform
Android SDK
Personal Analytics Website
Get in touch 10
ARGUS LABS PRESENTS
PUTTING MUSIC IN CONTEXT
Improving the listening experience through context-aware discovery.

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INTRODUCTION TO CONTEXT
In this day and age, consumers expect music providers to go beyond simple content delivery; they
expect a personalized experience that fits their lifestyle. In order to do this, music providers exhaust
market research methods in order to put their users into context. The issue with this process is
threefold: the strategies used are expensive; they don’t accurately measure behavior or habits;
and finally, they don’t provide continuous, real-time data. Yet context is crucial because without it,
“digital applications are deaf and blind,” says Richard W. DeVaul from Google X Labs [1]
.
The explosion of data in the last couple years has made it more challenging – and more imperative
– than ever to provide relevant and usable data to those who need it. There’s simply too much
personal information generated for basic analytic systems to provide knowledgeable feedback
about its users. Argus Labs, however, has established a contextualization platform that makes
sense of personal data and turns it into actionable knowledge, thereby providing better insights to
companies and individuals.
“ Without context, digital applications
are deaf and blind. ”
Richard W. DeVaul
Google X labs
[1] http://www.media.mit.edu/wearables/mithril/intro/topic3.html

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INTRODUCTION TO ARGUS LABS
In order to get increasing value out of big data, Argus Labs has built an intelligent contextualization
platform with robust context-aware tools that organize personal data into three pillars: habit, mood,
and environment. These three categories are layered on top of one another in order to create an
interconnected web of meaning about a person’s actions.
Instead of only providing the time of a specific event, which is the most common analytic variable,
Argus Labs’ context engine is aware of where a person is and where he is traveling, what music he
is listening to, how much sleep he got last night, along with a number of other information streams.
It puts specific individuals in context of the real world and understands their habits, moods, and
environment like never before.

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REAL-WORLD APPLICATIONS
The Argus Labs context engine actively transforms raw data into actionable knowledge and its
functionality is extremely versatile. Partnered companies and developers have the capability of
tapping into any number of our extensive user data streams in order to provide better insights about
audience and build a more streamlined experience for users.
The current process of analyzing a person’s music preferences depend almost entirely on listening
history and common interests shared with peers. The issue with this method is that the context of
the music session – how and why a person is listening – is left out entirely. When thinking about
all the different variables that go into someone listening to music, the industry is making mere
‘educated guesses.’ What about the device a person is using? Or their physical location? What
about the events that lead up to that moment? Even the weather? These are all insights that are
missing from the music industry’s current analytical framework. As a result, streaming services
do not tap into accessible data and use it to their advantage like they can with a contextualization
platform.
Shifting from a system that makes ‘best guesses’ to one that truly understands its user base and
has the ability to not only predict but also push recommendations makes a significant difference in
customer experience. Rather than having the user go online in search for new artists, the context
engine can predict music for an individual depending on their habits. Then, once the person begins
an activity – driving, working out, studying, etc – their device can push them the right content at the
right time. To the listener, it feels like magic because without any input, a person’s favorite music
tracks are suddenly streaming on their device just as they want them. It’s a innovative, streamlined
way to bring basic recommendations to an entirely new level.

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APPLYING CONTEXT - DATA FLOW

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The interconnected
information streams
that provide a
detailed view of who
a person is.
Broader segmentation of user
context into habit, mood and
environment profiles for a user.
Sample applications that could
be built on top of context profiles
to enhance an app’s user
experience.
USER CONTEXT CONTEXT PROFILE APPLICATION
HABIT MUSICAL EXCURSION ON HOLIDAY
• Music
• Location
• Activity
• user is travelling abroad
• user is listening to his favourite
genres
also
• user is visiting leisure places
• users is sleeping at a single
location throughout the trip
Suggest one or more local
music events that best
matches a person’s favourite
music genres and bands.
Send this message around
6PM when arrived in the hotel
where the user sleeps.
MOOD MUSIC MOOD FACILITATOR
• Music
• Location
• Social
• user is listening to music genre X
• genre X deviates from the user’s
normal listening behaviour
• genre x is associated with a strong
emotion Y
also
• user has changed Facebook
relationship status
Optimize the current playlist
to contain more songs
associated with genre X and
emotion Y. Avoid songs linked
to opposite emotions.
ENVIRONMENT EVENT WARMUP
• Music
• Location
• Schedule
• we know the user plans to attend
event X with taste-matching artists
Y
• user is currently at home listing to
the same taste of music
Adjust the music playlist to
include new and top tracks of
the artists performing to build
up to the event.
HABIT TAILORED TO YOUR COMMUTE
• Music
• Location
• Activity
• user is commuting to work
also
• the user’s monday morning
commute is 45 minutes on average
Optimize playlists to
incorporate favorite music
genres to create a better
listening atmosphere during a
commute.

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BENEFITS OF A CONTEXTUALIZED USER
EXEPERIENCE
FOR INDIVIDUALS
• Living music libraries that follow and adjust to you
• Unobtrusive, fluid listening environment at all times
• Self-learning system that creates playlists for every occasion and every mood
FOR MUSIC SERVICES
• Crystal clear understanding of customers
• Ability to tailor products and brands to certain demographics based on
interconnected data streams
• Content promotion (nearby concerts; music samples; advertising) that fits a
user’s lifestyle and schedule without annoyances builds loyalty
• Better targeting, engagement, and conversion rates
• Reduces churn of clients, which leads to more revenue
• Allows our partners to differentiate their products from competitors
• Privacy enhancing technologies, regulatory compliance and user trust on
everything we do with and without our partners

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TECHNICAL INTEGRATION
Argus Labs provides a suite of tools to enable both individual developers and corporate partners
and enterprises the ability to add contextual features to their products quickly and reliably.
CONTEXTUALIZATION PLATFORM
At the center of the Argus Labs offering sits an extensible and secure data aggregation platform.
This platform follows Linked Data principles and provides a RESTful API to developers to access
context histories as semantically-enriched data streams. Fine-grained permission controls allow
users to precisely define which parts of their context history are visible and to whom. This context
history serves as the basis on which more robust models and recommender systems can be trained
in the domain of a specific company. Additionally, Webhooks can be installed in the platform that
trigger when specific conditions are met regarding a user’s current context, obviating the need to
continuously poll the platform.
In a second phase, collective contextual analytics will be made available that group anonymized
contextual patterns together. These will allow developers and corporate partners to augment their
apps with broad context-aware features when individual context histories are not available.
ANDROID SDK
With the Argus Labs Android SDK, creating context-aware mobile applications has become easier
still. This library takes care of all boilerplate code necessary to securely connect to the Argus Labs
platform and start consuming contextual data streams. An extended version of the SDK that also
allows an end user to enable broader activity tracking on his smartphone and seamlessly stream
this to the platform is under continious development and available to corporate partners.
PERSONAL ANALYTICS WEBSITE
On top of the contextualization platform, we provide a personal analytics website designed for end
users. From here, they get a bird’s eye view of their context history and drill down with detailed
reports. Furthermore, it provides a completely transparent view of who can access their data and
how it is being used. A complete set of privacy controls empowers them to extend and withdraw
permissions on data access without jumping through hoops.

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GET IN TOUCH
Argus Labs is at the forefront of the evolution of analytics, offering a unique platform that is user
friendly for both individuals on the front-end and developers on the back-end. It’s robust and can
greatly improve the user experience in a number of scenarios. And on top of it all, it’s secure and
reliable. As the leader in the space, Argus Labs sees this as an opportunity and responsibility to set
a rigorous standard for a context-aware platform.
If you’re interested in exploring how Argus Labs can specifically meet your need, email us at
info@arguslabs.be or call us at our office +32 3 369 96 96.