About this Director, Customer Experience role at Hhaexchange
HHAeXchange is the leading technology platform for home and community-based care. Founded in 2008, HHAeXchange was born out of an idea to create a fully comprehensive end-to-end homecare solution to help people who are aging or have disabilities thrive in their homes and communities. Our employees are passionate about transforming the healthcare space by building the only homecare ecosystem that fully connects patients, personal care providers, managed care organizations, and states.
The Director of Customer Experience will own the strategy, architecture, and execution of a fully automated, AI-powered engagement model designed to drive product adoption at scale across our customer base and products. Reporting to the VP of Customer Experience, this role sits at the intersection of strategy, technology, and operations. You will design the systems and own the outcomes — from first-touch onboarding sequences to automated risk intervention, QBR delivery, and everything in between. This is a player-coach role: you will lead a team and be expected to roll up your sleeves on tooling, workflow builds, and data analysis.
This is a hybrid position, 3x a week in-office at our New York City office location.
To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.What You’ll Own
Tech-Touch CS Program Design & Scaling
- Architect and build the end-to-end tech-touch CS program for the SMB segment — define the engagement and adoption model, tooling stack, automation logic, and success criteria.
- Design tiered engagement strategies that account for customer lifecycle stage, product usage patterns, and business profile — without relying on high-touch human intervention for routine moments.
- Partner with Technical Customer Care to design and implement the operating model for how automated and human-assisted engagement intersect, including clear hand-off criteria and escalation paths.
- Build and manage agentic AI workflows that trigger personalized engagement nudges across email, in-app messaging, and chat based on real-time behavioral signals.
- Deploy automated outreach sequences that respond dynamically to product usage data — surfacing the right message, at the right moment, through the right channel.
- Implement AI-assisted outbound calling workflows that prioritize accounts by risk or opportunity and equip agents with contextual next-best-action guidance.
- Design just-in-time adoption experiences that adapt to a customer's role, use case, and activation stage — delivering the right training content when and where they need it.
- Build automated learning pathways that progress customers from initial setup through advanced feature adoption, with progress tracked and insights surfaced to leadership.
- Partner with the education and training teams to ensure content is structured for automated delivery and continuously updated based on product updates and adoption data.
- Develop and maintain a health scoring model that synthesizes product usage, engagement signals, support volume, and billing behavior into automated campaigns that drive adoption.
- Build AI-powered risk flagging workflows that identify churn precursors — disengagement patterns, missed milestones, usage drops — and trigger automated intervention before risk escalates.
- Define and implement automated hand-off protocols that route at-risk accounts to human CS or support teams when risk thresholds are breached, with full context packaged for the receiving team.
- Design and deploy automated QBR delivery for the SMB segment — generating account-level performance summaries, adoption benchmarks, and AI-drafted next-step recommendations without requiring manual preparation.
- Build the data pipelines and AI prompting logic needed to produce QBR outputs that are specific, actionable, and credible to the customer.
- Design the KPI framework — defining the metrics that matter (adoption rates, time-to-value, health score distribution, automated intervention outcomes, churn rate by cohort) and how they are tracked and reported.
- Build and maintain dashboards that give leadership a clear, real-time view of program performance and allow the team to identify optimization opportunities quickly.
- Establish a continuous testing and iteration cadence for engagement sequences, health score logic, and automation workflows.
Agentic AI Workflows & Automated Engagement
Personalized Onboarding & Adoption Journeys
Account Health, Risk Monitoring & Intervention
Automated QBRs & AI-Generated Recommendations
KPI Framework & Performance Measurement