Business Analyst, Customer Success Analytics & AI
Minnesota Staffing, Saint Paul, Minnesota, United States, 55130
Business Analyst, Customer Success Analytics & AI
We're looking for a Business Analyst, Customer Success Analytics & AI to help Customer Success leaders make faster, better decisions through actionable insights-and to shape how we use AI and Digital Customer Success to scale. This individual contributor role in Customer Success Operations blends strategic leadership with hands-on analysis, partnering closely with CS data teams (BI, Reporting & Insights, Data Operations) and CS stakeholders to turn reporting into clear recommendations and measurable next steps. About the Role
In your capacity supporting Customer Success analytics and AI enablement: Partner with CS leaders and cross-functional stakeholders to understand goals, pain points, and the decisions analytics must enable. Translate ambiguous requests into clear analytics requirements (scope, definitions, KPI logic, acceptance criteria, and rollout plans). Own a prioritized CS analytics/insights roadmap; manage timelines, dependencies, tradeoffs, and stakeholder communications. Coordinate delivery across BI, Reporting & Insights, and Data Operations to ensure high-quality, adopted outputs. Produce recurring and ad hoc insights across the CS lifecycle, including trend/driver analysis and executive-ready storytelling. Deliver crisp recommendations and actions (not just dashboards), highlighting opportunities, risks, and measurable next steps. Help define and execute Customer Success AI strategy: identify and prioritize AI use cases, size impact, assess feasibility/data readiness, and define measurement. Support responsible AI practices in partnership with IT/Security (governance, access controls, adoption). Build measurement and analytics frameworks to support Digital CS at scale (segmentation, funnel/journey views, play/program effectiveness, and capacity/coverage modeling). Guide teammates on data best practices (data quality, governance, and reporting standards). Leverage tools including Salesforce, Gong, Snowflake, Power BI, Tableau, Azure DevOps, Claude, ChatGPT, and Thomson Reuters AI tools to analyze data, automate insight generation, and deliver scalable reporting and enablement. Key Outcomes
Clear, decision-ready insights that drive action across the CS lifecycle (not just reporting). A well-managed, adopted analytics roadmap that improves CS prioritization and operational execution. Scalable Digital CS measurement (segmentation, alerts/exception-based management, journey visibility, program effectiveness). AI use cases delivered with defined value, governance, and measurable business outcomes. Strong cross-functional alignment across CS leaders, BI/Insights, Data Operations, and IT/Security. About You
You are a fit for this role if you have: 4-8+ years in Business Analysis, CS Ops/RevOps, Strategy & Ops, analytics, or similar roles blending stakeholder leadership and data-driven decision support. 1-2+ years using AI-driven analytics platforms or ML tools to deliver actionable business insights. Strong requirements gathering and stakeholder management skills; able to take problems from ambiguity to shipped deliverables. Proven ability to translate data into executive-ready narratives, recommendations, tradeoffs, and action plans. Analytical fluency: KPI design, segmentation/cohort analysis, driver analysis, funnel/journey thinking, and data quality awareness. Comfort working with technical partners to validate metric logic and data definitions (warehouse/BI context). Experience with AI/analytics tools such as Cursor, ThoughtSpot, DataRobot, H2O.ai (or similar). Nice to have: experience supporting Customer Success motions (adoption/health, renewals/expansion, onboarding), digital CS programs (tech-touch, lifecycle orchestration), and hands-on SQL/Snowflake or Power BI/Tableau reporting; experience implementing AI-enabled workflows with measurement, governance, and change management.
We're looking for a Business Analyst, Customer Success Analytics & AI to help Customer Success leaders make faster, better decisions through actionable insights-and to shape how we use AI and Digital Customer Success to scale. This individual contributor role in Customer Success Operations blends strategic leadership with hands-on analysis, partnering closely with CS data teams (BI, Reporting & Insights, Data Operations) and CS stakeholders to turn reporting into clear recommendations and measurable next steps. About the Role
In your capacity supporting Customer Success analytics and AI enablement: Partner with CS leaders and cross-functional stakeholders to understand goals, pain points, and the decisions analytics must enable. Translate ambiguous requests into clear analytics requirements (scope, definitions, KPI logic, acceptance criteria, and rollout plans). Own a prioritized CS analytics/insights roadmap; manage timelines, dependencies, tradeoffs, and stakeholder communications. Coordinate delivery across BI, Reporting & Insights, and Data Operations to ensure high-quality, adopted outputs. Produce recurring and ad hoc insights across the CS lifecycle, including trend/driver analysis and executive-ready storytelling. Deliver crisp recommendations and actions (not just dashboards), highlighting opportunities, risks, and measurable next steps. Help define and execute Customer Success AI strategy: identify and prioritize AI use cases, size impact, assess feasibility/data readiness, and define measurement. Support responsible AI practices in partnership with IT/Security (governance, access controls, adoption). Build measurement and analytics frameworks to support Digital CS at scale (segmentation, funnel/journey views, play/program effectiveness, and capacity/coverage modeling). Guide teammates on data best practices (data quality, governance, and reporting standards). Leverage tools including Salesforce, Gong, Snowflake, Power BI, Tableau, Azure DevOps, Claude, ChatGPT, and Thomson Reuters AI tools to analyze data, automate insight generation, and deliver scalable reporting and enablement. Key Outcomes
Clear, decision-ready insights that drive action across the CS lifecycle (not just reporting). A well-managed, adopted analytics roadmap that improves CS prioritization and operational execution. Scalable Digital CS measurement (segmentation, alerts/exception-based management, journey visibility, program effectiveness). AI use cases delivered with defined value, governance, and measurable business outcomes. Strong cross-functional alignment across CS leaders, BI/Insights, Data Operations, and IT/Security. About You
You are a fit for this role if you have: 4-8+ years in Business Analysis, CS Ops/RevOps, Strategy & Ops, analytics, or similar roles blending stakeholder leadership and data-driven decision support. 1-2+ years using AI-driven analytics platforms or ML tools to deliver actionable business insights. Strong requirements gathering and stakeholder management skills; able to take problems from ambiguity to shipped deliverables. Proven ability to translate data into executive-ready narratives, recommendations, tradeoffs, and action plans. Analytical fluency: KPI design, segmentation/cohort analysis, driver analysis, funnel/journey thinking, and data quality awareness. Comfort working with technical partners to validate metric logic and data definitions (warehouse/BI context). Experience with AI/analytics tools such as Cursor, ThoughtSpot, DataRobot, H2O.ai (or similar). Nice to have: experience supporting Customer Success motions (adoption/health, renewals/expansion, onboarding), digital CS programs (tech-touch, lifecycle orchestration), and hands-on SQL/Snowflake or Power BI/Tableau reporting; experience implementing AI-enabled workflows with measurement, governance, and change management.