System Design for Therapist Retention Analysis in an Online Mental Healthcare Application Based on MapReduce

Retention rate is an important factor for companies providing online services. They can measure potential gains and losses based on insights about their user retention rates. Such insights cover how many active users are, to those who stopped using the application. Based on these insights, companies can analyze the factors that affect user retention, so that they can take further action to minimize users who have the potential to stop using their services. Companies, such as those in the field of mental healthcare, can also develop better business strategies by considering the insights gained from the analysis. This research aims to design an information system to extract information from application usage data, to generate insights about user retention rates based on the metrics required by the company providing the application. The information system design is based on microservices architecture using MapReduce algorithm. The use of big data approach aims to facilitate the company's future needs as user data will grow continuously, as well as other benefits provided by the big data ecosystem. The design-to-testing phase is carried out by implementing an agile project management approach. The prototype successfully passed all testing phases according to acceptance test criteria, hence the information resulting from data processing can meet the company's needs.