One of the most important aspects of any search application is the ability to show relevant content that satisfies the needs of your users. Measuring relevance requires combining search results with the app side user interactions, and it can be hard to decide what to collect and how to do it. This is why we are excited to announce our new version of Search Traffic Analytics, a pattern on how to structure, instrument, and monitor search queries and clicks, that will provide you with actionable insights about your search application. You’ll be able to answer common questions, like most clicked documents or most common queries that do not result in clicks, as well as provide evidence for other situations, like deciding on the effectiveness of a new UI layout or tweaks on the search index. Overall, this new tool will provide valuable insights that will let you make more informed decisions.
Let’s expand on the scoring profile example. Let’s say you have a movies site and you think your users usually look for the newest releases, so you add a scoring profile with a freshness function to boost the most recent movies. How can you tell this scoring profile is helping your users find the correct movies? You will need information on what your users are searching for, the content that is being displayed and the content that your users select. When you have the data on what your users are clicking, you can create metrics to measure effectiveness and relevance.