Research in the field of information retrieval and recommendation mostly focuses on one single evaluation method and one single quality objective. On the one hand, many research endeavors focus on system-centric evaluation from an algorithmic perspective and consider the context of use only to a minor extent. On the other hand, there are research endeavors focusing on user-centric approaches to the design and evaluation of systems. However, algorithmic quality and perceived quality of user experience do not necessarily match. Thus, it is essential for system evaluation to substantially integrate multiple evaluation methods that cover a variety of relevant aspects and perspectives. Only such an integrated combination of methods may lead to a deep understanding of users, their behavior, and experience in their interaction with a system. This half-day tutorial follows the objective to raise awareness in the CHIIR community concerning the significance of using multiple methods in the evaluation of information retrieval and recommender systems. The tutorial illustrates the ‘‘blind spots’’ when using single methods. It introduces the concept of ‘‘multi-method evaluation’’ and discusses its benefits and challenges. While multi-method evaluations may be designed very flexibly, the tutorial presents broadly-defined basic options of how multiple methods may be integrated in an evaluation design. In group work, participants are encouraged to select and fine-tune a specific design that best matches their research endeavor’s purpose.