Analyzing Therapy Practice Client Behavior and Acquisition
About the Project:
This project focused on addressing key issues faced by a therapy practice, specifically targeting the problem of no-show appointments. The client, who owns the practice, was concerned about the frequency of missed appointments and sought to understand the characteristics of these clients to mitigate the issue. Additionally, the project aimed to identify the ideal customer profile to enhance the practice's client acquisition strategy.
Using anonymized data to ensure client and patient privacy, I conducted a thorough analysis to uncover patterns and trends. The analysis revealed several factors contributing to no-show appointments, such as appointment times, client demographics, and booking behaviors. By identifying these characteristics, I provided the client with actionable insights to implement strategies that could reduce no-show rates.
Furthermore, I analyzed the data to determine common traits among the most reliable and engaged clients. This information was used to create a targeted marketing strategy, helping the client attract and retain ideal customers.
Technologies Used: Python, pandas 2, matplotlib.
Note: Some information pertaining to the client and patients has been redacted or modified for privacy reasons.
Project link on Google Colab