Transcript
Page 1: Putting Music in Context

PUTTING MUSICIN CONTEXT

Improving the listening experience through context-aware discovery.

JULY 2013

www.arguslabs.beby R. Berger, D. Damen, K. Underseth and A. Wuyts

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TABLE OF CONTENTS Introduction to context 3 Introduction to Argus Labs 4 Real-world applications 5 Applyingcontext-dataflow 6 Benefitsofacontextualizeduserexperience 8 For individuals For music services Technical Integration 9 ContextualizationPlatform Android SDK Personal Analytics Website Get in touch 10

ARGUS LABS PRESENTS

PUTTING MUSIC IN CONTEXTImproving 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 applicationsare 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 matchesaperson’sfavouritemusic genres and bands. Send this message around 6PMwhenarrivedinthehotelwhere 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

Optimizethecurrentplaylistto 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 includenewandtoptracksoftheartistsperformingtobuildup 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

Optimizeplayliststoincorporatefavoritemusicgenres 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,fluidlisteningenvironmentatalltimes

• 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 auser’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 PLATFORMAt 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 SDKWith 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 WEBSITEOn 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.

Ifyou’reinterestedinexploringhowArgusLabscanspecificallymeetyourneed,emailusat

[email protected]+3233699696.


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