Staff Analyst, Marketing Analytics & Audience Insights

ServiceNow is a leading company focused on AI-driven business reinvention. The Staff Analyst, Marketing Analytics & Audience Insights role is responsible for measuring marketing program performance, driving analytics for audience targeting, and ensuring data integrity across marketing efforts.

Responsibilities:

• Own program performance measurement. Build and run recurring reviews tracking coverage, engagement, and pipeline contribution by solution and geo, from raw data through to the 'so what' for VP and SVP audiences
• Drive buying group analytics. Measure coverage, engagement, and progression across solutions. Track role composition to surface gaps and expansion opportunities, and translate findings into account targeting and One Teams strategy
• Own audience segmentation end to end. Translate targeting requirements and campaign objectives into the account and contact dataset that powers dashboards and campaigns. Set and defend the logic for how audiences get built, prioritized, and refreshed, and surface the insights that shape go-to-market decisions
• Bridge marketing intent and data reality. Understand what a campaign is trying to accomplish, then build the segments and measurement that serve that goal, not just what's easy to query
• Present to senior leadership. Compress complex analyses into clear narratives for VP and SVP stakeholders. You're in the room to drive a decision, not just deliver a deck
• Partner closely with data engineering. Translate ambiguous stakeholder questions into clear specs for pipelines, refresh cycles, and dashboards, and hold the standard for what 'done' looks like
• Steward the data responsibly. Maintain a clean, well-defined, and compliant audience dataset. Work within privacy guardrails, enforce no-PII activation standards, and keep the dataset trustworthy as accounts and ownership evolve
• Be the source of truth for marketing data. Own and defend the definitions, write the documentation, and enable stakeholders so the dataset is used correctly, not misread or misapplied