Customer Analytics Manager

Job Overview

The Customer Analytics Manager will own core analytics used to evaluate customer health, engagement, satisfaction, product adoption, configuration quality, and growth potential.

You will work with raw usage and configuration data, develop trusted analytical models, conduct detailed investigations, and present decision-ready insights to Customer Success leadership and cross-functional partners.

Key Responsibilities

• Build and maintain customer health scoring models covering risk, engagement, and satisfaction signals throughout the customer lifecycle.
• Develop data models that measure product usage and adoption across the customer base.
• Provide Customer Success, Support, and leadership teams with reliable visibility into how customers use the platform.
• Conduct ad-hoc and deep-dive analyses for Customer Success, Sales, and Product stakeholders.
• Translate complex analytical findings into clear recommendations and practical next steps.
• Create and maintain product configuration metrics that compare customer deployments with recommended practices.
• Identify and model upsell, cross-sell, and expansion opportunities within existing accounts.
• Estimate the addressable value of customer growth opportunities.
• Partner with Customer Success Operations, Sales, Product, and Data teams to maintain consistent analytics definitions and infrastructure.
• Help ensure customer analytics remain trusted, accurate, and usable across the organization.
• Present insights and recommendations to Customer Success leadership in a concise, decision-ready format.

Required Qualifications

• At least 60 months of experience in analytics, data science, business intelligence, or a closely related field.
• Relevant experience supporting Customer Success, Revenue, or similar commercial teams within a SaaS organization.
• Advanced SQL skills.
• Hands-on experience building data models in a modern cloud data warehouse.
• Experience with platforms such as Snowflake, Databricks, or BigQuery.
• Proficiency with business intelligence or data visualization tools such as Sigma, Tableau, or Looker.
• Demonstrated experience building and maintaining customer health score models.
• Experience using customer health models to support proactive Customer Success action.
• Experience creating product usage, adoption, or configuration metrics from raw product telemetry or usage data.
• Track record of identifying and estimating upsell, cross-sell, or account expansion opportunities.
• Ability to work effectively with both technical data models and executive-level presentations.
• Strong communication skills and the ability to convert complex analysis into a clear business narrative.

Preferred Qualifications

• Experience with Customer Success platforms such as Gainsight.
• Familiarity with Gong or Pendo.
• Hands-on experience building AI-supported analytical workflows.
• Experience using tools such as Glean agents or Claude skills to automate analysis.
• Bachelor’s degree in Statistics, Economics, Computer Science, or another quantitative discipline.

Core Analytics Focus

• Customer health scoring.
• Product usage and adoption analytics.
• Customer configuration analysis.
• Revenue expansion modeling.
• Upsell and cross-sell opportunity sizing.
• Customer lifecycle analytics.
• Business intelligence reporting.
• Executive-level data storytelling.
• Customer Success Operations.
• Cross-functional data governance.

Technical Skills

• Advanced SQL.
• Modern cloud data warehouses.
• Snowflake.
• Databricks.
• BigQuery.
• Sigma.
• Tableau.
• Looker.
• Data modeling.
• Product telemetry analysis.
• Business intelligence dashboards.
• AI-powered analytics workflows.

Work Arrangement

• Remote position within the United States.
• Member of the Customer Success Operations organization.
• Regular collaboration with Customer Success, Sales, Product, and Data teams.
• Frequent communication with senior leadership regarding customer trends, risks, and growth opportunities.

Compensation

The annual base salary range for this position is $107,100 to $154,000.

Actual compensation will be determined using factors including relevant skills, experience, qualifications, and geographic location. The role may also qualify for bonus or incentive compensation, equity, and a broader benefits package.

Hiring Process and AI Use

Abnormal AI uses AI-assisted recruiting tools to help interviewers prepare questions and identify areas to explore based on resume content and job requirements.

These tools do not automatically screen applicants or make hiring decisions. Candidate decisions are made by people.

The company may conduct video interviews, validate applicant identity during the recruitment process, and require successful completion of pre-employment checks before issuing a final offer.

About Abnormal AI

Abnormal AI develops a behavioral AI cybersecurity platform designed to protect organizations and their employees from AI-powered cybercrime. More than 4,500 enterprises use the company’s technology to help detect and prevent sophisticated email and account-based threats.