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Senior Manager, Customer Analytics

Senior Manager, Customer Analytics

AIA Group
Fresher
Not Disclosed
  • Posted 2 months ago
  • Be among the first 10 applicants

Job Description

Create connections that move people and business forward.




About the Role


. Serve as the primary business SME for customer analytics, acting as the bridge between Marketing, Business Units, Data Science, Data Engineering and Technology teams.
. Define and operationalize customer data foundations, ensuring customer, behavioral, marketing and transaction data are standardized, automated and scalable across Business Units.
. Partner with the Director of Customer Analytics & Insights to develop and maintain the roadmap for customer analytics products, including lead scoring, propensity models, next-best-action, upsell, cross-sell and customer value models.
. Translate business requirements into analytical solutions and data products that drive customer acquisition, engagement, retention and repurchase outcomes.
. Support the industrialization of customer analytics by establishing scalable processes, automation frameworks, reporting solutions and model deployment standards.
. Ensure customer analytics capabilities are effectively embedded into business processes, marketing activation and customer engagement programs across the region.

Roles and Responsibilities:

Customer Analytics Product Management

  • Partner with the Director to define and prioritize the customer analytics product roadmap across Group and Business Units.
  • Act as the product owner for customer analytics use cases, ensuring alignment between business priorities and technical development.
  • Manage requirements gathering, business case development and stakeholder alignment for customer analytics initiatives.
  • Monitor adoption, effectiveness and business impact of analytics products and recommend enhancements where required.
  • Coordinate delivery across Data Science, Data Engineering, Martech and Technology teams.

Data Foundation & Automation

  • Define customer data requirements, frameworks and governance standards to support analytics use cases at scale.
  • Partner with Data Engineering and Technology teams to establish automated, reliable and scalable data pipelines.
  • Drive improvements in customer data quality, accessibility and integration across multiple data sources.
  • Support the development of Group-level data assets that enable consistent reporting, modelling and activation across markets.
  • Ensure customer data structures are designed to support future personalization, predictive analytics and AI-driven use cases.

Predictive Models & Customer Intelligence

  • Support the development and deployment of customer analytics products including:
    • Lead scoring models
    • Propensity-to-buy models
    • Cross-sell and upsell models
    • Repurchase propensity models
    • Customer lifetime value models
    • Customer segmentation frameworks
  • Translate business objectives into model requirements and success metrics.
  • Work with Data Science teams to ensure models are explainable, actionable and operationally scalable.
  • Establish processes for monitoring model performance, adoption and commercial outcomes.

Business Partnership & SME Leadership

  • Serve as the primary customer analytics SME for Group Marketing and Business Units.
  • Work closely with local business teams to identify opportunities where analytics can drive measurable business value.
  • Translate complex analytical concepts into practical business recommendations for senior stakeholders.
  • Facilitate alignment between business, technology and analytics teams throughout project delivery.
  • Support markets in embedding customer intelligence into campaign planning, customer engagement and retention initiatives.

Reporting & Performance Measurement

  • Develop and maintain customer analytics dashboards and measurement frameworks.
  • Deliver regular performance reviews and business impact assessments to Group leadership.
  • Identify opportunities to improve customer acquisition efficiency, retention performance and customer value.

Job Requirements:

  • Bachelor or Post-Graduate degree or at least 15 years experienceon Life Insurance and Financial Services especially in Marketing
  • Direct/ hands-on experience and proven success in driving customer repurchase especially at a regional level is compulsory
  • Actuarial background especially technical knowledge and experience in product development and pricing an advantage
  • Excellent communication skills, both written andverbal
  • Sound understanding of insurance related financialmetrics
  • Sound data and analyticsexperience
  • Strong business acumen and analytical thinking, reflected in impact and influence skills and confidence in high level interactions with theleadership team
  • Strategic Thinking, planning and executionskills

Key Skills

Customer Data Quality

Cross-sell and Upsell Models

Lead Scoring Models

Customer Lifetime Value Models

Propensity-to-Buy Models

Data Pipelines

Repurchase Propensity Models

About Company

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