Posts Tagged ‘relevancy’

Increasing Relevancy of Recommendations with Human Pyramid – Part 1

Sunday, April 11th, 2010

When building a recommendation site, product or service, there are six human layers you can pile on top of pure data-based relevancy. To define the scope of ‘recommendation product’ more clearly, any search service is a recommendation service. Google is recommending websites to the user based on the search term and the page ranks, meta data and inbound links to the relevant websites. If a user gives input to a website and the website then returns output based on that input, then it is a recommendation service. The 6 layers are illustrated in the pyramid below, with the top level being the most accurate, but also usually the hardest to accurately achieve.  In this post, I’ll discuss the bottom 3 layers, while saving the top 3 layers for tomorrow’s post.

Recommendation Pyramid - Personalized, Social, Community

I’ll use the example of a ‘Recent Releases’ dvd movie site to illustrate the 6 pyramid levels. Without the pyramid, the site would show the 90 most recently released dvds, either alphabetically or chronologically. Instead of making the user sift through all 90 titles and make a decision based solely on name, plot, genre, cast and crew, we can add some or all of the layers below to filter the list to the most relevant releases and give the user more data to use when making a decision. This increases the signal:noise ratio, which is an important meta strategy for the web as a whole, as the internet is full of noise and getting noisier each day with tweets and status updates and blogs and microblogs, etc. Filtering through all of the content on the web to find what is relevant and useful to you will be of growing importance and solutions to this problem will be a big part of the next phase of the web.