This chapter provides an overview of advancements in psychotherapy research and practice enabled by the Experience Sampling Method (ESM), an innovative approach for tracking mental health complaints through repeated assessments of affect, cognition, behavior, and contextual factors. Conducted primarily through smartphone apps, ESM enhances traditional mental health assessment methods by reducing retrospective bias and fostering greater patient engagement, awareness, and self-management. Although ESM’s clinical applications show promise, more evidence is needed to support its widespread use in psychotherapy. This chapter highlights pioneering projects, TheraNet and Therap-i, which have integrated personalized ESM-based feedback into clinical settings. These initiatives demonstrate how individualized ESM protocols, including adaptive question sets and visual data feedback, can deepen case conceptualization and assist in therapy planning. Illustrative case studies detail how personalized ESM approaches supported therapeutic processes in patients with complex mental health conditions, such as depression and attention deficit hyperactivity disorder (ADHD). The chapter discusses insights from these case examples, emphasizing the value of personalized assessment in promoting psychoeducation, treatment planning, and outcome tracking. In the discussion, we provide some recommendations for ESM implementation in clinical research and practice. Key considerations include balancing personalization with standardization, integrating social and contextual data, addressing data privacy, and adapting to diverse therapeutic and health care systems. We conclude with practical advice for the clinical adoption of ESM and discuss the potential impact of this method in enhancing patient-centered mental health care.