Manager Of Product And Client Analytics

Your Role and Impact

Skills

• Advanced analysis in Excel and Google Sheets.
• Strong knowledge of SaaS business models and metrics.
• 7+ years in analytics; 5+ years in customer success or operations (preferred).
• Proven track record of data-driven projects with measurable business impact.
• Excellent presentation, communication, and active listening skills.
• Strong interpersonal and influencing abilities; able to build trust and foster collaboration.
• Empathetic and adaptable, with the ability to prioritize and manage multiple projects.

• Deep understanding of the healthcare landscape, market trends, and client challenges.
• Familiarity with the mental wellbeing market, including key needs and pain points.

• Strong analytical skills: building, interpreting, and presenting customer data and ROI.
• 2+ years in customer success, consulting, or similar client-facing roles.
• Experience collaborating across cross-functional teams.
• Bachelors degree preferred.
• Proven ability to manage multiple priorities with attention to detail.

Role Overview

The Manager of Product and Client Analytics will lead the development of a robust reporting framework, working closely with Product, Engineering, Client Success, and Sales teams to deliver actionable insights that drive business goals and client outcomes. This role will oversee the integration of product performance with client utilization and engagement, build standardized dashboards, ensure high-quality reporting databases, and provide strategic insights into user behaviors and feedback.

Responsibilities

• Collaborate with Product and Engineering to define reporting requirements, trackable events, and manage the reporting roadmap.
• Partner with Product and Engagement teams to analyze trends, user interactions, and journey touchpoints.
• Standardize and enhance reporting capabilities, closing analytics gaps to improve efficiency and impact.
• Contribute thought leadership to align analytics with business goals and strategic priorities.
• Foster collaboration between Data Analytics and QA teams to ensure data accuracy and quick issue resolution.