Recommendations
From Social Patterns
Contents |
Example
Amazon recommends media for me based on my past buying habits as well as on similarities between my behaviors on those of other customers.
What
In the search for relevancy and quality, people have a difficult time zeroing in on satisfactory content.
When
Offer recommendations when you have a sufficient body of data about your user's self-declared and implied interests as well as a rich enough social graph to be able to identify similarities and make helpful guesses about likely interesting content.
How
Offer a call to action inviting the user to explore recommendations. Educate the user about how to obtain better recommendations (for example, by rating content).
Display recommendations as a list, or if there are a large number, in a carousel, or scrollable window.
Netflix bases recommendations primarily on your past behavior, but it factors in social data as well, when it has any.
Twitter suggests users for you to follow. If you're just starting, they don't know your preferences yet, so they're either going on popularity, some other quality metric, or paid placement.
Why
Recommendations push objects toward people rather than relying on them to be passively discovered. If you can provide value to your users by making educated guesses about the type of objects they are interested in, then you may be able to capture their loyalty. The benefit to users is more readily finding the information and media they need without having to hunt around for it quite so hard.
Related Patterns
As Seen On
- Netflix
- Amazon
- Digg
- Seeqpod
- The Filter
- StumbleUpon
Sources
- Social Media
- Social Objects
- Tuning In
- Filtering
- Recommendations
- Social Search
- Pivoting
