When you try to gauge how effective your website is, you may decide upon certain metrics to measure its impact. Those may differ based upon the objectives of your pages, but could include things like how many orders you receive for products you might offer, how many phone calls you receive inquiring about your services, how many people signup for newsletters or subscribe to your RSS or click upon ads on your pages. They could include whether people link to your pages, or tweet or +1 articles or blog posts that you’ve published. You may start looking at things like bounce rates on pages that have calls to action intended to have people click upon other links on that page. You could consider how long people tend to stay upon your pages. There are a range of things you could look at and measure (and take action upon) to determine how effective your site might be.
A search engine is no different in that the people who run it want to know how effective their site is. A patent granted to Yahoo today explores how the search engine might evaluate pages ranking in search results for different queries, and looks at a range of possible measurements that it might use. While this patent is from Yahoo, expect that Google and Bing are doing some similar things. And while Bing is providing search data for Yahoo, that doesn’t mean that Yahoo’s results might not be presented and formatted differently than Bing’s results, and include additional or different content as well. As a matter of fact, Yahoo recently updated its search results pages.
One of the problems or issues that you might run into when attempting to see how well your site works is determining how well the metrics you’ve chosen to measure that might work. A problem that plagues large sites is that they are so large that it can be difficult to determine which metrics work best. Yahoo’s approach uses a machine learning approach to determining the effectiveness of different “search success” metrics.