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Jobber is seeking a Senior Customer Analytics Manager to join its Strategy & Analytics department as a senior individual contributor. This role partners with business leaders across the organization to drive data-informed decisions on customer behavior, growth opportunities, and long-term customer value.
Reporting to the Senior Manager of Customer Analytics, you will own one or more high-priority customer analytics domains spanning acquisition, onboarding, lifecycle engagement, product adoption, monetization, retention, expansion, and customer success. This is an individual contributor leadership role—you will not manage people directly, but will lead through influence, mentor analysts, shape analytical roadmaps, and manage senior stakeholder relationships.
Key responsibilities include:
• Lead strategic customer analytics and insights as an internal consultant, helping stakeholders clarify business questions, evaluate opportunities, and measure performance across the customer journey.
• Conduct deep-dive analyses on funnel performance, customer segmentation, conversion, engagement, product usage, retention, expansion, and long-term value drivers.
• Define, refine, and govern critical KPIs for assigned domains, ensuring metrics align with business outcomes and customer quality.
• Translate ambiguous business questions into structured analytical approaches, decision frameworks, and actionable recommendations.
• Evaluate the impact of strategic initiatives, operational changes, go-to-market motions, product launches, and customer programs.
• Build analytical understanding of assigned domains, identifying opportunities to improve growth, efficiency, customer experience, and durable value.
• Support strategic planning, forecasting, target setting, business cases, and resource allocation decisions.
• Drive experimentation and measurement strategies for A/B tests, pilots, campaigns, and lifecycle programs.
• Apply advanced analytics techniques including impact evaluation, scenario analysis, simulation modeling, forecasting, segmentation, and predictive analytics.
• Partner with Data Science on complex modeling opportunities such as customer scoring, churn propensity, and AI-assisted workflows.
• Build trusted relationships with senior leaders and cross-functional teams (Revenue Operations, Strategy, Marketing Analytics, Product, BI & Analytics Engineering).
• Communicate insights through clear, executive-ready narratives that connect analysis to business decisions and outcomes.
The ideal candidate brings strong business acumen, deep analytical expertise, excellent communication skills, and the ability to influence decisions at multiple organizational levels.
