Product Director, Customer Experience & Product Analytics

Altana is the network for trusted trade, empowering governments and businesses to build a more resilient and secure global economy. As a Director of Customer Experience and Product Analytics, you will own the customer experience from onboarding to adoption, ensuring that customer feedback is integrated into product development and driving improvements across the user journey.

Responsibilities:

• Define and continuously improve the full customer lifecycle: first touch, sales handoff, onboarding, activation, adoption, expansion, network activation, and renewal
• Define the platform and experience for omni-channel support, AI native support, and the feedback loop of how support makes our customer experiences and product itself better
• Identify friction in the customer journey — with data, with empathy, and with ruthless prioritization — and coordinate with other product and engineering teams to eliminate it
• Build the rituals and mechanisms that keep Altana's customer experience responsive to a rapidly evolving product, without adding process overhead that slows the team down
• Partner with Sales, Customer Success, and Product to ensure every stage of the customer lifecycle is designed intentionally, not inherited by default
• Design and operate an AI-powered system that continuously synthesizes signals from customer conversations, support tickets, NPS responses, and usage patterns into structured, actionable product intelligence
• Replace ad hoc "customer said this" updates with a living, queryable knowledge base that sales, product, and engineering teams can access directly — integrated into the development process, not appended to it
• Automate the synthesis of customer feedback into roadmap inputs: surface themes, flag anomalies, and generate prioritized briefs for product teams without requiring manual curation
• Champion a culture where customer insight is a first-class artifact — as trustworthy and retrievable by AI agents as it is by humans
• Own the product analytics infrastructure: instrumentation strategy, event taxonomy, dashboard design, and the metrics that actually matter
• Identify and manage against KPIs for usage growth and network growth (K factors, TTV, PQLs, etc)
• Define and track the leading indicators of customer health — activation depth, feature adoption, workflow completion — not just lagging indicators like churn and NPS
• Build predictive models that surface at-risk customers before they escalate and identify expansion opportunities before they're missed
• Translate behavioral data into clear, compelling narratives for the executive team — not just charts, but decisions
• Build an in-product, agentic customer support capability: deliver in-product, multi-lingual support agents and own the underpinning knowledge bases, technical documentation, SOPs, and communication/routing infrastructure to enable agentic and human follow ups and execution
• Arm the Customer Success team with AI-assisted tooling: automated account summaries, usage anomaly alerts, renewal risk scores, and AI-generated briefings that let CSMs focus on high-value conversations rather than manual research
• Coordinate with marketing and sales to build scalable, 1:many engagement programs that deliver personalized product guidance, release updates, and educational content based on customer segment, use case, and lifecycle stage
• Reinvent how Altana communicates product changes: transform release notes from compliance artifacts into clear, customer-centric narratives that drive adoption — distributed through the right channels at the right moment in the customer journey
• Define the tooling stack (CRM, customer success platforms, analytics, AI agents) and own its integration into a coherent, data-rich operating system
• Build the structures so every product manager and engineer serves as the voice of the customer at product planning. Your efforts will make this signal frictionless to access and analyze
• Build the feedback loop between how customers receive product updates and how those updates are prioritized — creating a system where customer adoption data informs the next sprint, not just the next quarterly review