# Predictive churn model helps a plastics manufacturer prioritise sales engagement

> A multinational plastics packaging manufacturer · Industrial & Aviation

A multinational plastics packaging manufacturer needed to anticipate customer churn so its sales team could act before mid-tier accounts drifted away. A bespoke, explainable churn model gave sales a real-time view of which customers were most at risk.

## What was the problem?

The manufacturer wanted to manage churn by anticipating risk at the individual customer level so its sales team could pre-empt likely losses. Its customer base was diverse, with different data sources and behavioural patterns, and churn was non-contractual and hard to predict. The business needed a model that was credible, easily explainable to the sales team and demonstrably effective, and that integrated with its enterprise resource planning and customer relationship management systems and an automated dashboard.

## What did QuantSpark do?

We hypothesised the potential drivers of churn and applied statistical techniques to customer-level order histories, behavioural patterns and periodicities, building a consistency index of order regularity to flag customers whose future order volumes were likely to fall. Because churn was non-contractual, we used statistical methods to quantify the risk associated with particular order behaviours, detecting changes in order volume that were often small yet strongly correlated with future churn, and weighted risk by behavioural signals such as recent service experience. We focused on the mid-tier customers who a time-constrained sales team would otherwise underserve, then productionised the model within the client's existing systems and fed risk scores automatically into its CRM and dashboards for sales teams across every region.

## What changed?

The model reliably identified customers at higher risk of churn from their recent behaviour, giving the sales team a real-time view of churn propensity and the leading indicators behind it. Sales could prioritise outreach to previously underserved mid-tier accounts and manage churn more deliberately, and the engagement built wider confidence in analytics across the organisation.

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