Improving Customer Retention

Churn/Retention

$2 BI

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$4.3 MI

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73%

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Goal

A marine telecommunications provider was facing issues with customers churning at the point of migration to a new technology. The goals of the project were to better understand drivers of churn and migrations and to provide leads in order to prioritise efforts from the commercial team.

Approach

• Ran a rapid diagnostic to understand the value at stake and validate feasibility.

• Used an existing playbook template as a jumping-off point and customized it to specific churn and migration contexts.

• Connected previously isolated data sources, including customer characteristics, consumption, and external data, and created a new vessel entity that defined the unit of analysis.

• Built multiple machine learning models (explanatory and predictive) and integrated them into a modeling pipeline, delivering insights through existing dashboards.

Interventions

• Explanatory model: Extracted qualitative insights, helping to characterize churners and migrators.

• Predictive model: Provided leads used by sales teams to prioritize commercial efforts.

• Model outputs were integrated with in-house BI dashboards and CRM solutions, giving users access to data-driven insights and facilitating the feedback loop.

• Results from the pilot showed a 4x increase in migration rates for the prioritized leads compared to the baseline.

• Undertook a talent assessment, presenting a series of recommendations to consolidate the new capability, including recommended team structure, recruiting best practices, training and handover to the team.