Customer Intelligence Product Manager

Datascience

DataScience Middle East is looking for a Customer Intelligence Product Manager that will be responsible for defining, building, and scaling next-generation Customer Value Management (CVM) and Customer Intelligence platforms. This role owns the end-to-end product vision and execution of AI-driven, real-time customer engagement ecosystems, enabling hyper-personalized interactions across all customer touchpoints.

Key Responsibilities
br>Product Strategy & Vision

• Define and own the Customer Intelligence & CVM product roadmap, aligned with enterprise growth, CX, and revenue objectives.
• Lead the evolution from batch campaign management to real-time, event-driven decisioning.
• Build a vision for hyper-personalized, AI-powered customer engagement at scale, leveraging predictive analytics and behavioral insights.
• Position the platform as a central decisioning layer across all marketing, digital, and customer interaction channels.br> br>Customer Intelligence & Data Activation
• Design and operationalize unified customer profiles, combining behavioral, transactional, and contextual data.
• Enable advanced segmentation, audience management, and dynamic audience activation across channels.
• Ensure seamless data-to-decision pipelines, allowing real-time activation without latency or dependency on heavy data movement .
• Drive capabilities around:
• Customer 360 & identity resolution
• Event-based triggers and streaming data utilization
• Continuous audience enrichment and refreshbr> br> br>Campaign Management & Journey Orchestration
• Lead the design of end-to-end campaign management frameworks supporting:
  
  • Multi-channel campaigns (digital, branch, contact center, retail, etc.)
  • ATL & BTL orchestration
• Build and manage intelligent customer journeys:
  
  • Multi-step, multi-touchpoint journeys
  • Real-time and scheduled interactions
  • A/B/n testing and journey optimization
• Enable AI-assisted journey creation and automation, reducing manual effort and accelerating time-to-market .br> br>Real-Time Decisioning & Next Best Action
• Own the development of a real-time decisioning engine that determines:
  
  • Next Best Action (NBA)
  • Next Best Offer (NBO)
  • Channel & timing optimization
• Translate business strategies into decision logic, rules, and AI models.
• Enable marketer-led decisioning frameworks, allowing business users to deploy strategies without heavy IT dependency .
• Ensure decisions are:
  
  • Context-aware
  • Event-driven
  • Continuously optimized through feedback loopsbr> br>AI, Personalization & Automation
• Embed AI and machine learning into all layers of the product:
  
  • Predictive modeling (churn, propensity, CLV)
  • Personalization engines
  • Reinforcement learning for optimization
• Drive hyper-personalization at scale, delivering tailored experiences across channels.
• Leverage AI assistants, copilots, and autonomous agents to:
  
  • Automate campaign creation
  • Recommend strategies
  • Optimize engagement performance .
• Champion self-learning systems that continuously improve outcomes.br> br>Omnichannel Engagement & Communication
• Ensure seamless orchestration across all customer touchpoints:
  
  • Digital (mobile, web, app)
  • Outbound (SMS, email, push notifications)
  • Inbound (call center, chatbot)
  • Offline (branch, retail, field)
• Define and enforce contact policies and communication governance to optimize customer experience and avoid fatigue .
• Enable right-time, right-channel delivery for every interaction.br> br>Product Delivery & Execution
• Work closely with:
  
  • Data Scientists
  • Data Engineers
  • Martech teams
  • Business stakeholders
• Translate business requirements into:
  
  • Product features
  • User stories
  • Technical requirements
• Lead agile product development cycles, ensuring fast delivery of incremental value.
• Oversee integration with:
  
  • Core systems
  • Digital channels
  • External ecosystemsbr> br>Performance, Optimization & Value Realization
• Define and track KPIs and success metrics:
  
  • Conversion rates
  • Campaign ROI
  • Customer engagement metrics
  • Revenue uplift
• Enable closed-loop measurement frameworks:
  
  • Feedback-driven optimization
  • Experimentation (A/B/n testing)
• Continuously improve customer journeys and decision models based on insights.br> br>Stakeholder & Business Alignment
• Engage with senior stakeholders (Marketing, CX, Digital, Sales).
• Act as a trusted advisor on customer intelligence transformation.
• Lead workshops to define:
  
  • Use cases
  • Customer strategies
  • Personalization frameworks
• Drive adoption of data-driven decision-making culture.br> br>