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17 MARCH 2014

The Pandora Music Genome Project

"We believe that each individual has a unique relationship with music–no one else has tastes exactly like yours. So delivering a great radio experience to each and every listener requires an incredibly broad and deep understanding of music. That's why Pandora is based on the Music Genome Project, the most sophisticated taxonomy of musical information ever collected. It represents over ten years of analysis by our trained team of musicologists, and spans everything from this past Tuesday's new releases all the way back to the Renaissance and Classical music.

Each song in the Music Genome Project is analyzed using up to 450 distinct musical characteristics by a trained music analyst. These attributes capture not only the musical identity of a song, but also the many significant qualities that are relevant to understanding the musical preferences of listeners. The typical music analyst working on the Music Genome Project has a four–year degree in music theory, composition or performance, has passed through a selective screening process and has completed intensive training in the Music Genome's rigorous and precise methodology. To qualify for the work, analysts must have a firm grounding in music theory, including familiarity with a wide range of styles and sounds.

The Music Genome Project's database is built using a methodology that includes the use of precisely defined terminology, a consistent frame of reference, redundant analysis, and ongoing quality control to ensure that data integrity remains reliably high. Pandora does not use machine–listening or other forms of automated data extraction.

The Music Genome Project is updated on a continual basis with the latest releases, emerging artists, and an ever–deepening collection of catalogue titles.

By utilizing the wealth of musicological information stored in the Music Genome Project, Pandora recognizes and responds to each individual's tastes. The result is a much more personalized radio experience – stations that play music you'll love – and nothing else."

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TAGS

analysing dataappeal • attributes • automated data extraction • characteristicsdata analysisdata gathering instruments • data integrity • databasedescriptive labels • ersonalised radio experience • frame of reference • individual preference • individual taste • internet radio • listener preference • machine-listening • metricsmusic • music analyst • Music Genome Project • music taste • music theory • musical characteristicsmusical identitymusical information • musical preferences • musicological information • musicologist • Pandora Radiopersonal taste • precisely terminology • qualities • quality control • radio • radio experience • redundant analysis • relatednesssegmentationsongtaste (sociology)taxonomy • unique taste • user behavioursuser segmentation

CONTRIBUTOR

Simon Perkins
22 AUGUST 2013

Re-imagining segmentation in Google Analytics

"One of the most popular and powerful features in Google Analytics is Advanced Segmentation. It lets you isolate and analyze subsets of your traffic. You can select from predefined segments such as 'Paid Traffic' and 'Visits with Conversions' or create your own segments with a flexible, easy–to–use segment builder. Then, you can apply one or more of these segments to current or historical data, and even compare segment performance side by side in reports.

We've recently re–imagined segmentation to make it even easier for new Analytics users, yet also more powerful for seasoned analysts and marketers."

(Google Inc)

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TAGS

2013analysing dataanalysis dataanalyticsanimated explainer video • cohort analysis • cohort segmentation • cohort studies • compare segment performance • customersdata gathering instrumentsdemographics • Google Analytics • Google Inchistorical datamarket segmentationmetricsmetrics toolsreports • segment builder • segmentation • site behaviours • sub-segment • subset • traffic analysistransaction datatrend analysisuser behavioursuser demographicsuser groupsuser segmentationwebsite traffic statistics

CONTRIBUTOR

Simon Perkins
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