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Music recommendations Bjørn Tennøe – FAST Global Services – March-October 2007

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Presentation on theme: "Music recommendations Bjørn Tennøe – FAST Global Services – March-October 2007"— Presentation transcript:

1 Music recommendations Bjørn Tennøe – FAST Global Services – March-October 2007 bjorn.tennoe@fast.no

2 2 Use design resources to create end user value Defining value for the end user Peter Moreville Value 62% 28%48% Tangibles (usefulness) 36% 56% 13% UsabilityPrice 62% 32% 18%16%47% 18% Brand Range of investments Tools and calculators Information content Navigation Speed Help/ Tutorials Admin Fee Transaction Fee End users’ perception of value Quantitative survey and regression analysis Research by Phase 5 for undisclosed financial institution

3 3 Adapt to the users’ mind set External GUI, branding Internal Data model, organization Bjørn Tennøe Make your service thrive by adapting it to the user’s mind set. Don’t alienate users by mirroring the service to the organization & data model.

4 4 Recommendations are key to online media services –Online media services offer vast content collections. –Most of the media collection is unknown to the consumer, and therefore the user must get recommendations to make best use of the collection. Subscription services without recommendations have lower traction with consumers. Also media stores benefit greatly from recommendations, in addition to premium editorial content. –Recommendations can be social, editorial or search powered (personalized). While SDP supports all approaches, this presentation focuses on search powered recommendations.

5 5 Some recommendation benefits –Drives consumers away from Top 20 Guide towards higher margin items, avoid DRM issues –Offers “convenience” as an alternative to “free” The potential of “convenience” is not fulfilled –Introduces new service types Last.fm Pandora

6 6 Types of search powered recommendations –Item to item, non personalized: Consumers of item A also consumed items B, C… –Collaborative filtering, personalized: People that have habits similar to you, and that consumed item A, also consumed items B, C… –Research: Sequences: Given that track A is desirable, find tracks B, C… that are appropriate to follow.

7 7 Who benefits most from recommendations? Serendipitous  Genre sensitive  Picky  Target users for recommendations

8 8 Example approach: Integration with overall service –The example on the following pages are centered around recommendations for an online music subscription service. –A recommendations interface with a library/playlist structure allows seamless integration with the overall service. –Recommendations in the library should  narrow down the library to something the user can relate to. –Recommendations in the playlist should  expand discover something new. –Recommendations in the player should  offer alternatives to the current style. Library Use recommen- dations to  narrow down PlayerUse recommendations to  explore alternatives Playlist Use recommendations to  expand

9 9 Search powered music player Demos available on www.tennoe.no/FAST

10 10 Mobile music player with recommendations Choose sourceExpand from source Demos available on www.tennoe.no/FAST Start page w/ recommendationsPlay screen with escape paths

11 11 More recommendation demos Demos available on www.tennoe.no/FAST

12 12 Keep the interface as simple as possible –Avoid metadata based navigation whenever possible. Rather, let the user navigate by (example) content. Analogy: Advanced versus simple search interfaces. –Does the user care about data type? Can “Performing Artist”, “Conductor” and “Playlist” be presented in the same result set?

13 13 A note on normalization –For music collections: Normalize and simplify the user’s track metadata for better findability in the library. Sort songs by “Nelli Futhado” and “Nelly Furtado feat. Justin Timberlake” under “Nelly Furtado”. A Berliner Philarmoniker CD may be found both under Karajan (the conductor), Mutter (the violinist) and Bach (the composer). In such cases, the decision on what metadata to display depends on frequency. All tracks must be represented with minimum 1 entry (artist/playlist) in the library.

14 14 Way forward –FAST’s user experience team can: Contribute with design specifications Offer best practice & guidance to peer design teams Facilitate creative workshops & quality control activities Assist in prototyping

15 Thank you


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