An approach to internal search query ana...

Course Hero is an education technology company that provides subscription services for accessing crowd-sourced study materials. Our business is driven by SEO and having the most selective student generated materials related to a course. We show a small preview of the content to the search engines, which gets indexed. When users search any long-tailed education related queries for which our content is relevant, our content link would show up among the top results. This is how our product gets visibility. We have 3 main types of content on our website: student generated study documents, Q&A, and flashcard sets. Our internal search functionality is the method by which our customers discover content on our website. Content consumption and engagement metrics provide insightful information about the relevancy of our internal search algorithm and the quality of our content repository. Data mining these metrics helps us understand what our customers' demands are and how well our product is catering to them. Using unstructured search query data, as well as structured consumption and engagement metrics, we mined a meaningful list of high value content categories that yielded a sizeable traffic increase. As a part of the talk, we will be going over the analytical methodology for mining and identifying these high value categories.