Churn Prediction (Coworking)
Nexudus, a leading provider of software for coworking spaces, faced the challenge of managing customer loss in a global database. Customer turnover posed a threat to revenue stability and customer satisfaction, making a solution urgent to identify attrition patterns and effectively optimize retention strategies.
At WhiteBox, we developed a churn prediction model using technologies such as Python, Airflow, Pyspark and LightGBM. This model analyzes a wide variety of data, including contract details, monthly activities (reservations and check-ins), demographics and rate variations, to identify patterns that predict churn risk. The solution not only identifies at-risk customers, but it also provides insights to design personalized strategies that improve retention and reduce revenue loss.
The project allowed Nexudus to anticipate customer desertion with great precision, improve retention strategies based on concrete data and customize actions towards different customer segments. As a result, revenue stability was increased, the user experience was optimized, and Nexudus's position as a leader in global coworking management was strengthened.
