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In this study, we present the implementation of an early warning system in a large introductory statistics module which is escalated over four semester offerings. An early warning system identifies students who are at risk of failing or dropping out of a module, and provides them with supporting interventions. While familiar undergraduate mathematics supports include formative assessment and peer-assisted learning, our interventions tried to encourage student engagement through personalised emails which detailed supports and how students were progressing in the module. In later escalations, at-risk students received weekly emails encouraging them to use the Maths Support Centre. We believe our module-based interventions had limited impact upon the at-risk students. In hindsight, we believe these students needed programme-level interventions. Overall, this study provides insights for others into implementing learning analytics interventions.