Trust and Authority of Intranet Sites to Improve Search


Trust and Authority of Intranet Sites to Improve Search
Photo by Eric Ziegler
My trek reading through Google Semantic Search book continues with some insights into trust and authority of pages and sites. I continue to see search engine optimization similarities between what happens in the internet and what should be happening in the enterprise. For instance, in this note, the idea of a page or site being authoritative can be applied directly to helping employees find content in sites that are created in a company intranet.  

Inside the enterprise, often there are many different types  of "sites". These sites range from sites or pages for policies, sites where projects occur, reference material sites, self help sites, business procedures sites and community sites. And for each of these sites, the level of authority of trust associated with each site varies. In addition, these trust scores vary based on the subject or topic of the site.

For example the policy pages/sites should have a high trust/authority score, since they are basically the rules the company and employees need to follow.  A site for a project should have a much lower trust or authority score. Project sites typically are working on future state ideas, and do not represent the current state.  Just imagine what could happen if an employee were to read and use content on a project site to answer an customers question.

Similarly, sites that are for communities of practice should have a higher trust / authority score for the subjects they are centered around. The Java community site should have a high trust / authority score on the Java topic. The customer support community should have a high trust / authority score on customer support. etc.

By improving the authority of specific sites, especially around subjects, the findability and discoverability of sites increases, making every employee's life in the enterprise that much better and makes each of them more effective.

This note was inspired by +David Amerland 's book, Google Semantic Search.