Content creators often see writing good titles and applying the correct taxonomy terms as a nuisance. They care more about producing content than about how others consume it. Even training may not help. However, advances in machine learning may finally give us a way to out of this predicament.
Search technology includes taxonomy management, text analytics, search analytics and more. These related technologies add meaning and intelligence and make the search experience more efficient and enjoyable.
Context acts as a guide who knows you and your circumstances. However, context does not come out-of-the-box; you need to design for it. And when you get it right, context can make search delightful.
Search will not magically make sense of messy content. You need to transform or model the content to serve user needs and boost search relevancy. Only then can search work its magic.
Search interfaces need to be designed to meet goals and top tasks. Using an out-of-the-box or default interface will not deliver the effectiveness or satisfaction that people so desperately demand of enterprise search.
Studying users will help surface dominant personas and their top search tasks. The findings can help you take your search from a drab, out-of-the-box offering to a specific and effective search experience.
Search goals bring the design process into focus. They help you make the right decisions and create opportunities for new ideas and solutions. By not defining goals, you risk creating generic, out-of-the-box search experiences that let down your users and your business.
An experience is what a person goes through and remembers. A search experience, therefore, is a person's feelings and memories of using search. People embrace pleasant experiences and reject awful ones. Experiences, however, are hard to design. They depend on many factors. The first step is to uncover and unpack them.
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