Industry: Community Led Local Development
Company Size: Small (10-49)
Technology Type: Internet Services & Applications
Services Provided: Test Before Invest
Introduction
Our Fundraiser provides a fundraising service to charitable and philanthropic community organisations including schools, parishes, charities, and community groups aiming to raise money for their local initiatives.
Individuals sign up and contribute a recurring weekly payment to enter themselves into a weekly fundraising draw. This platform helps to reduce the workload associated with fundraising, while offering an easy to use, engaging pay to support initiative that allows supporters the opportunity to win prizes. However, as the platform grew, Our Fundraiser began to face a challenge common to many subscription-based services: customer churn.
Challenges
Customer churn refers to the loss of existing customers over a period of time for any reason at all. This was especially the case amongst families signed up through primary and secondary school programmes. Predictable patterns began to emerge e.g. where a pupil approached the end of their time in the school, parents would cancel their subscription. This created a predictable but significant loss of subscribers each year, impacting fundraising stability for participating organisations. Our Fundraiser came to CeADAR to explore how data analytics and artificial intelligence could help them better understand their customer base and identify subscribers who might be at risk of cancelling their subscription. The goal was to move from a reactive approach to customer retention towards a more proactive and data-driven strategy.
The Solution
CeADAR worked with Our Fundraiser to develop a machine learning solution capable of predicting the likelihood that a customer would cancel their subscription within the following 30 days. The model analyses multiple sources of historical data, including customer profiles, subscription history, and payment activity. By identifying patterns in this data, the system can detect behavioural signals that may indicate an increased likelihood of churn. Each week, the system generates an updated churn risk score for every subscriber. Customers are categorised into Low, Medium, or High-risk groups, to quickly identify those most likely to cancel their subscription.
This output is delivered in a simple and accessible format that allows the Our Fundraiser’s team to easily review customer risk levels and prioritise engagement efforts.
Results and Benefits
The machine learning model acts as an early warning system, helping Our Fundraiser identify customers who may be considering cancelling their subscription before it happens. By transforming existing customer, payment and transaction data into actionable insights, Our Fundraiser can now take targeted steps to improve retention. For example, at-risk customers can be prioritised for communication campaigns or engagement initiatives.
The solution enables Our Fundraiser to move beyond reactive customer management and instead adopt a proactive, data-driven retention strategy.
Key benefits included:
- Early identification of churn risk, enabling proactive engagement with customers
- Improved use of existing data, transforming historical customer information into predictive insights
- Targeted retention strategies, allowing marketing and engagement efforts to focus on the customers most likely to churn
- Scalable and automated analysis, providing updated insights on a weekly basis without increasing operational workload
By using AI and advanced analytics, Our Fundraiser now has a clearer understanding of customer behaviour and a practical tool to help strengthen long-term engagement with their subscriber community.
