Boosting Customer Retention in the Leisure Industry

Case Study

About our  client

The leisure company’s success is built around a flexible membership model. With that flexibility comes the challenge that members can cancel their membership without warning. In these circumstances, boosting customer retention is a critical driver of success. The company wanted a data science partner that would focus on delivering value from investments and to help it to develop a stronger analytical culture internally. As specialists in delivering value through data-driven decision making, Mango Solutions partnered with the leisure company to help it create descriptive, diagnostic and predictive insights that have delivered measurable value with a significant return on investment (ROI).


In a highly competitive marketplace, the leisure company were interested to find out which of their members were most likely to cancel their membership in the near future. This awareness would enable the business to create tailored marketing campaigns that target the right members at the right time and support retention efforts. This strategy would ensure healthier and more stable membership numbers, which would contribute to the firm’s continuing success and growth.

While some membership loss is inevitable in a highly competitive market, it was believed that retention performance could be further improved. The company recognised that a data-driven solution was a key enabler to successfully overcome this challenge.

However, the company didn’t have its own internal data science capability and developing a strategic partnership with a consultancy that could bring external data science expertise therefore became essential. The company wanted its partner to work closely with its internal data and analytics team to deliver successful projects with measurable ROI.


In line with the leisure company’s requirement to build internal capability, an experienced team of data science consultants with strong technical and analytic skills, alongside Rich Pugh, Mango’s Chief Data Scientist, provided strategic advice to the company including the Executive Team. Mango consultants worked in partnership with the company’s data and analytics team, but also spent significant time working across areas of the business to understand day-to-day operations and decision-making processes.

In partnership with the client, Mango used a range of machine learning and other data science techniques to build a range of statistical models with measurable and provable ROI. Mango used its proprietary framework to review the requirements put forward by the leisure company and proposed a plan to deliver them. This included an assessment of the quality of the company’s data, its internal data expertise and technological infrastructure, as well as a plan to cover the proposed solution from data collection and preparation through to predictive modelling and monitoring model performance. The effectiveness and performance of models was evaluated against historical data. Mango continued to iterate and improve the modelling efforts in response to new data and by adding enhancements such as feature engineering.


The project has had a positive impact by helping the leisure company to understand member behaviours and to establish the right capabilities to deliver data-led change. The company is now able to target the members with tailored marketing campaigns boosting customer retention, which has delivered significant business value through data science, with a proven and measurable ROI. Mango continues to work with the company and this relationship is helping the company to deliver value from data across a variety of business areas, including the potential impact of alternative models and associated marketing interventions.

Working with the Mango team has been an exciting and immersive experience. The quality of the data science team members is very high, and the working style has been one of partnership. Early metrics show that the initial project has delivered ROI in excess of 100% and we will continue to work strategically to agree further areas of collaboration” – Company Head of Data & Artificial Intelligence