Okta
SeniorManager,RetentionStrategy&Intelligence
“Senior Manager, Retention Strategy & Intelligence at Okta. Skills: Retention Strategy, Intelligence, AI/ML, data architecture, APIs, risk signals, recommendation engine, tooling, field cadences. Own definition, tracking, and interpretation of customer risk signals including usage, engagement, sentiment, and commercial health.. Partner with TDI to establish signal weighting, scoring thresholds, and supporting data infrastructure.”
What You'll Achieve.
Model Quality: Risk scores and recommendations achieve >80% accuracy with field feedback on actionability.; Tooling Adoption: High, sustained engagement across field teams.; Recommendation Acceptance: Measurable lift in retention outcomes where AI recommendations are followed.; Cadence Effectiveness: Cadences running consistently with improvement in early risk identification.; Revenue Impact: ARR at risk stabilized and recovered through program interventions.; Roadmap Delivery: On-track execution against FY'27 milestones with a Phase 2 plan in place.
Industry & Context.
solve complex challenges with real-world stakes; Conduct root cause analysis on churn and contraction to identify gaps and inform future iterations.
in-person onboarding experience
What They're Looking For.
Must Have
7+ years across Customer Success, Renewals, Sales Enablement, or Revenue Operations with hands-on experience in data, analytics, or process automation., Working knowledge of AI/ML, data architecture, and APIs., Able to engage technical teams and translate business needs into solutions., Able to design the logic and guardrails that govern AI behavior and ensure outputs are accurate and operationally useful., Connects data signals to customer realities and understands how field teams actually work., Experience defining requirements, managing roadmaps, and iterating on user feedback., Able to influence and align across Engineering, Data Science, Sales, CS, and Renewals.
What You'll Do.
and interpretation of customer risk signals including usage
and commercial health.
Partner with TDI to establish signal weighting
and supporting data infrastructure.
Translate risk analysis into clear
actionable intelligence for field teams and leadership.
Define the guidelines
and decision logic that govern AI-driven retention recommendations.
Partner with TDI and Data Science to build models that generate personalized playbook recommendations based on account context
Evaluate recommendation quality and drive model refinement where AI output and business reality diverge.
Own product requirements for risk and recommendation tooling
and outputs that make AI recommendations actionable for field teams.
Manage the roadmap from pilot to GA
prioritizing enhancements based on field feedback and model performance.
Ensure integration with CRM
and existing tools to minimize friction and drive adoption.
Design and lead recurring risk review cadences
including customer health reviews
that drive systematic action on AI-generated signals.
Embed cadences into Territory Planning
and renewal cycles through clear workflows and supporting materials.
Serve as the primary field advocate
ensuring recommendations reduce cognitive load and drive decisive action.
Track performance across signal accuracy
recommendation acceptance
and retention outcomes.
Establish feedback loops with field teams and TDI to continuously refine model logic and system design.
Conduct root cause analysis on churn and contraction to identify gaps and inform future iterations.
How You'll Work.
Team & Collaboration
partner directly with our Renewals organization; collaborating with GTM functions across the customer lifecycle; partnering with our Technology, Data, and Insights (TDI) team; Partner with TDI to establish signal weighting, scoring thresholds, and supporting data infrastructure.; Partner with TDI and Data Science to build models that generate personalized playbook recommendations based on account context, risk type, and lifecycle stage.; Ensure integration with CRM, ERP, and existing tools to minimize friction and drive adoption.; Establish feedback loops with field teams and TDI to continuously refine model logic and system design.; Cross-Functional Leadership: Able to influence and align across Engineering, Data Science, Sales, CS, and Renewals.
Communication Scope
Translate risk analysis into clear, actionable intelligence for field teams and leadership.; Serve as the primary field advocate, ensuring recommendations reduce cognitive load and drive decisive action.
Process & Methodology
Manage the roadmap from pilot to GA, prioritizing enhancements based on field feedback and model performance.
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