Embed Size (px)
Citation preview
2
Use design resources to create end user value
Defining value for the end userPeter Moreville
Value
62%
28%48%
Tangibles(usefulness)
36%
56%
13%
Usability Price62%
32%18% 16% 47%
18%
Brand
Range ofinvestments
Tools andcalculators
Informationcontent
Navigation
Speed Help/Tutorials
AdminFee
TransactionFee
End users’ perception of value Quantitative survey and regression analysis Research by Phase 5 for undisclosed financial institution
3
Adapt to the users’ mind set
ExternalGUI, branding
InternalData 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
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
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
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
Who benefits most from recommendations?
Serendipitous Genre sensitive Picky
Target users
for recommendations
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
Player Use recommendations to explore alternatives
Playlist
Use recommendations to expand
9
Search powered music player
Demos available on www.tennoe.no/FAST
10
Mobile music player with recommendations
Choose source Expand from source
Demos available on www.tennoe.no/FAST
Start page w/ recommendations Play screen with escape paths
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
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
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
Thank you
