Senior Analyst, Customer Experience

Overview 2. GENERAL JOB SUMMARY The Senior Analyst, Customer Experience is accountable for the overall success, health, and retention of a portfolio of customers in a post-sale capacity. This role combines customer relationship management with technical and operational oversight to ensure customers achieve expected business outcomes. The CXM owns the full customer journey post-sale, including customer outcomes, support experience, and risk management, and serves as the primary point of accountability for customer outcomes. The CXM is an AI-first role, leveraging AI, automation, and data-driven signals to manage customer engagement at scale, prioritizing orchestration and decision-making over manual execution.

The role works cross-functionally with Product Engineering (Support / Dev), Product Management, Professional Services, Customer Advocates, and Sales to deliver a consistent, high-quality customer experience across assigned accounts. 3. SCOPE Knowledge: Deep expertise in assigned products, industry domain, and customer use cases. Strong understanding of enterprise software environments, configurations, integrations, and data flows. Proficiency in interpreting AI-generated insights and usage metrics. Complexity: Manages a portfolio of B2B software/SaaS customers of varying size and complexity. Scope and complexity increase by level (Associate through Director). Requires judgment in prioritizing direct engagement versus AI/program-led approaches. Supervision: No direct reports in most scenarios; varies by region and level. Operates with significant autonomy, escalating cross-functional issues as appropriate. 4. ORGANIZATION Full Line: None (in most scenarios; varies by region) Dotted Line: Account Manager; Customer Advocate; Product Engineering (Support & Dev); Services; Product Management; AI as a Service teams 5. PRINCIPAL DUTIES AND

RESPONSIBILITIES Customer Ownership & Outcomes • Own overall customer health, retention, and satisfaction across assigned accounts. • Build and maintain strong relationships with key customer stakeholders, including executive sponsors. • Ensure customers realize value from their investment. AI-Driven Customer Management • Leverage AI tools and platforms to monitor customer health, engagement, and risk signals. • Utilize AI-generated insights to prioritize actions and determine appropriate engagement models. • Continuously identify opportunities to improve efficiency and customer experience through AI and automation. Escalation & Risk Management • Lead customer escalations end-to-end, ensuring timely resolution and clear communication. • Identify early risk signals (NPS detractors, adoption gaps, support trends) and drive mitigation plans. • Own follow-up and action planning for NPS detractors, ensuring concerns are addressed with closed-loop communication. • Coordinate cross-functional teams to resolve complex technical or operational issues. Engagement • Drive targeted customer engagement using scalable, programmatic approaches. • Leverage AI-driven content, campaigns, and enablement resources to guide customers on best practices. • Deliver structured engagements (e.g., business reviews) for higher-tier customers where appropriate. Support Experience Oversight • Oversee the AI-enabled support experience for assigned customers, ensuring issues are resolved effectively. • Partner with Support and Engineering to address recurring issues and improve product quality. • Ensure alignment between customer expectations and service delivery. Expansion Support • Identify growth opportunities through customer engagement, product usage insights, and AI-driven signals. • Partner with Account Management and Sales to support expansion and renewal activities. • Provide input on customer strategy, risks, and opportunities as assigned. Performance Measures Success is measured by customer outcomes rather than operational activity. Key performance indicators include: • Customer Retention (Gross Retention): Achievement of gross retention targets and reduction of churn across assigned accounts. • Customer Health: Improvement and maintenance of customer health scores, including proactive identification and mitigation of risk. • Customer Satisfaction (NPS): Management of customer sentiment, including ownership of NPS detractor follow-up, root cause identification, and recovery actions. • Escalation Management Effectiveness: Timely and effective resolution of customer escalations, including coordination across internal teams and clear communication with stakeholders. • Expansion Support: Identification and progression of growth opportunities in partnership with Account Management and Sales. Role Boundaries To ensure clarity and scalability, the CXM role is focused on outcome ownership and does not directly execute all aspects of the customer lifecycle. This role: • Does not act as primary support delivery, but oversees AI-enabled support outcomes and leads escalations when needed. • Does not carry a sales quota, but partners with Account Management and Sales to identify and support growth opportunities. • Does not perform onboarding activities, but engages QuickStart Consultants and Professional Services when customers require onboarding or adoption support. • Does not perform repetitive, manual activities, instead leveraging AI, programs, tools, and automation to drive engagement at scale. 6. JOB SPECIFICATIONS Education: Bachelor's degree preferred. Equivalent combination of education and experience will be considered. Work Experience: Proven experience managing customer relationships in a B2B software or SaaS environment. Experience with enterprise software (ERP strongly preferred). 5- 7 years of experience in Customer facing role with above experience. Knowledge, Skills & Abilities: • Effective communication skills, including ability to engage executive stakeholders. • Demonstrated ability to manage complex customer situations and drive outcomes. • Strong technical aptitude with ability to understand software architecture, integrations, and data flows. • Demonstrated desire and ability to learn and apply AI tools in day-to-day work. • Ability to interpret AI-generated insights and apply judgment in decision-making. • Strong problem-solving, critical thinking, and data-driven decision-making skills. • Ability to manage multiple customers and priorities effectively. • Understanding of relevant industry domains (e.g., manufacturing, supply chain, food & beverage).