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CVM Specialist - Prepaid Retention & Loyalty

Duración: Full-time

Región: South Africa

Modo: On-site

Tarifas: TBD

Se ha cerrado esta oportunidad.

El puesto ya no está disponible. Seguiremos trabajando para ofrecerte oportunidades mejor adaptadas.

Descripción

Our client, a leading telecom provider with operations across Africa and the Middle East, is looking for an expert to implement a base management strategy for its prepaid mass segment.

The role:

  • Drive the execution of all Proactive & Reactive Retention which will maximize the prepaid customer’s lifetime value through extending tenure and growing revenues.
  • Identify & address the root cause of churn to sustain churn reduction by geo location.
  • Uses predictive analytics and complex event processing to quickly take the right action to mitigate the potential risk or convert the opportunity.
  • Provide input into the overall CVM business strategy, specifically the Consumer business unit by ensuring the prepaid CVM strategy and its commercial deliverables are aligned and supporting of the overarching business goals.
  • Forecast, track, and report Prepaid churn & design effectiveness plan to mitigate Risky customers.
  • Manage prepaid customer retention and tenure through an integrated approach that include inflow management and retention campaigns.
  • Design Churn Predication, inactivity, Multi SIM and RFM models to proactively retain customers.
  • Perform channel mix optimisation for base development activities.
  • Drive and optimise channel execution by setting volume and value targets based on the approved prepaid budget.
  • Manage Service churn in order to prevent customer’s overall inactivity.

Experiencia profesional

  • Min 3-5 years of relevant work experience
  • Fluent in English and other South African Languages
  • Experience in CVM methodology, principles, capabilities, and techniques.
  • Demonstrated ability to create, lead and inspire high-performing teams.
  • Prior experience of mobile industry preferably  Prepaid Retention.
  • Experience with research- and analytics-driven quantitative pricing techniques (e.g. choice modelling)

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