Digital Performance Manager

Infor is looking for an experienced, analytically rigorous Digital Performance Manager to join our Marketing Analytics team, working closely with the hiring supervisor, on B2B performance analysis. This role owns performance measurement across the full digital funnel - from website and paid media engagement through form fills, MQLs, sales opportunities, and pipeline - and will work closely with the Paid Media team, the Web team, and marketing leadership to get there. You'll be the connective layer between top-of-funnel digital activity and downstream revenue outcomes, translating fragmented data from web, paid, and CRM systems into a coherent view of what's driving (or holding back) growth. This is a senior, largely self-directed role: you'll be trusted to define the analytical approach, not just execute against a spec.

A Typical Day in the Life Includes:

• Own end-to-end funnel analytics - connect web, paid media, and AI/LLM-driven engagement to form fills, MQLs, opportunities, and closed-won pipeline, identifying where and why prospects convert or drop off, and use AI tooling to accelerate diagnostics and reporting turnaround.
• Own web analytics using GA4, Looker Studio, and related tooling - actively monitor organic, direct, and referral channels alongside on-site conversion and content/landing page performance, and own visibility and traffic from AI/LLM search surfaces (e.g., AI Overviews, ChatGPT, Perplexity) as an emerging discovery channel - while continuously improving tracking fidelity (event tracking, UTMs, GA4 configuration, tagging governance).
• Own paid media analytics across paid search, paid social, and programmatic/display - surface reallocation opportunities, testing recommendations, and efficiency actions across channel and campaign performance, audience/creative testing, and attribution across a multi-touch buyer journey.
• Build and maintain the reporting and dashboard layer that gives marketing and sales leadership a single, trustworthy view of funnel health, channel ROI, and pipeline contribution - designed for executive consumption, not just raw output - and document methodology and definitions so metrics stay consistent as the team scales.
• Drive conversion-rate diagnostics and CRO - form and test hypotheses on where and why prospects drop off, and partner with the Web team and business stakeholders to recommend and implement fixes, rather than reporting findings in isolation.
• Own data integrity end-to-end - partner with the Paid Media team, Web team, marketing leadership, RevOps, content, design, and engineering to close tracking and data-quality gaps across the Paid Media platforms → GA4 → CRM → data warehouse chain; audit and reconcile discrepancies across GA4, ad platforms, Salesforce, and the data warehouse, and build monitoring so issues are caught before they reach a dashboard.

Basic Qualifications:

• Experience in digital/marketing analytics, with ownership of both web analytics and paid media analytics.
• Experience connecting top-of-funnel web/paid data to downstream outcomes - form fills, MQLs, sales opportunities, and pipeline/revenue.
• Experience with Ad Platforms, GA4 and Looker Studio (or equivalent BI tooling), including custom configuration, not just report consumption.
• Experience with CRM/marketing data (e.g., Salesforce, marketing automation platforms) and how funnel stages are defined and tracked.
• Understanding of digital marketing channels (SEO, paid search, paid social, display/programmatic, email) and how they interact across the funnel.
• Experience in a B2B or account-based marketing environment.
• Legal authorization to work permanently in the United States for any employer without requiring a visa transfer or visa sponsorship.

Preferred Qualifications:

• Experience with multi-touch attribution or marketing mix modeling.
• Experience with Snowflake or a similar cloud data warehouse, and integrating Salesforce data into it.
• Familiarity with tag management systems (e.g., Google Tag Manager) and server-side tracking.
• Strong SQL skills and experience querying and modeling data in a data warehouse environment.
• Experience building or working with Python/R for deeper statistical or diagnostic analysis.