Over the past decade, search engines have not only improved the quality of search results, but also evolved in how they interact with users. Modern search engines provide assistance to users throughout the entire search process, from formulating their information needs to presenting results and recommending additional content. This chapter presents a selection of topics, where entities are utilized with the overall aim of improving users' search experiences. First, in Sect. 9.1, we discuss techniques for assisting users with articulating their information needs. These include query assistance services, such as query autocompletion and query suggestions, and specialized query building interfaces. Next, in Sect. 9.2, we turn to the question of result presentation. In conventional document retrieval, the standard way of serving results is to display a snippet for each document, consisting of its title and a short summary. This summary is automatically extracted from the document with the aim of explaining why that particular document is relevant to the query at hand. Moving from documents to entities as the unit of retrieval, the question we need to ask is: How can one generate dynamic summaries of entities when displaying them as search results? Finally, in Sect. 9.3, we describe entity recommendation methods that present users with contextual suggestions, encourage exploration, and allow for serendipitous discoveries. We study the related entity retrieval problem in different flavors, depending on what kind of input is available to the recommendation engine. Furthermore, we address the question of explaining the relationship in natural language between entities presented to the user. We refer to Table 9.1 for the notation used in this chapter. 9.1 Query Assistance Chapter 7 dealt with query understanding from the machine's point of view. In this section, we bring the user's perspective to the forefront. How can a semantic search