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Lead Product Manager - Marketing Attribution & Performance
Summary
At UKG, the work you do matters. The code you ship, the decisions you make, and the care you show a customer all add up to real impact. Today, tens of millions of workers start and end their days with our workforce operating platform. Helping people get paid, grow in their careers, and shape the future of their industries. That's what we do.
We never stop learning. We never stop challenging the norm. We push for better, and we celebrate the wins along the way. Here, you'll get flexibility that's real, benefits you can count on, and a team that succeeds together. Because at UKG, your work matters-and so do you.
About the team
UKG is transforming how Marketing measures performance, optimizes investment, and demonstrates its impact across the sales and opportunity funnel.
You'll work at the intersection of Marketing strategy, business process, data, analytics, and product management. You'll partner with Marketing, Marketing Operations, Sales, Finance and Financial Planning and Analysis (FP&A), Enterprise Data and Analytics, Data Science, Technology, Privacy, and Architecture to build trusted products that connect marketing activity and investment to engagement, pipeline, opportunities, revenue, and business outcomes.
About the role
As Lead Product Manager, Marketing Attribution & Performance, you'll own the product vision, strategy, roadmap, objectives and key results (OKRs), and measurable outcomes for Marketing Attribution and Performance.
You'll define how UKG measures marketing-sourced and marketing-influenced impact using first-touch, last-touch, multi-touch, incrementality, and Media Mix Modeling approaches. You'll also help leaders understand what performed, why it performed, where measurement is limited, and where to invest next.
In this role, you will:
+ Translate business and analytical needs into prioritized epics, features, user stories, acceptance criteria, and release plans.
+ Lead discovery, minimum viable product (MVP) definition, sequencing, dependency management, delivery, adoption, and continuous improvement.
+ Build a capability roadmap spanning measurement, identity, data products, reporting, experimentation, and decision intelligence.
+ Define the enterprise measurement framework for marketing-sourced and marketing-influenced pipeline, opportunities, bookings, revenue, and return on investment.
+ Develop and govern first-touch, last-touch, and multi-touch attribution models with clear business rules, assumptions, limitations, and explanations.
+ Partner with Data Science and Analytics on incrementality testing, holdouts, lift methodologies, experimentation, and Media Mix Modeling.
+ Connect campaign, content, channel, audience, spend, engagement, marketing-qualified lead (MQL), business development representative (BDR) engagement, opportunity, pipeline, bookings, and revenue data.
+ Define key performance indicator (KPI) hierarchies, semantic definitions, attribution windows, opportunity-association logic, source rules, and performance benchmarks.
+ Deliver reporting and analytical products that explain performance by program, campaign, channel, audience, segment, geography, funnel stage, and investment.
+ Define product requirements for identity resolution across anonymous IDs, cookies, device and digital IDs, hashed identifiers, known person and account IDs, customer relationship management (CRM) records, and opportunity entities.
+ Partner with Data and Analytics and Architecture on canonical data models, identity-stitching rules, data lineage, quality thresholds, reconciliation, observability, and governed data products.
+ Ensure campaign source, channel, content, audience, cost, program, and other critical metadata are captured and retained through the customer and revenue journey.
+ Balance measurement goals with privacy, consent, security, platform constraints, data latency, and maintainability.
+ Identify responsible uses of generative and agentic artificial intelligence (AI) to automate analysis, surface anomalies, explain performance, recommend investments, and improve decision velocity.
+ Establish appropriate human oversight, governance, explainability, and controls for AI-supported analysis and recommendations.
+ Drive adoption through enablement, documentation, governance, feedback loops, and clear accountability for data and process quality.
+ Communicate product strategy, measurement approaches, roadmap decisions, model limitations, risks, and outcomes to executives, marketers, analysts, engineers, and sales leaders.
Success in this role will include:
+ A governed view of marketing performance from investment and activation through pipeline, opportunities, bookings, and revenue.
+ More consistent attribution, identity coverage, data quality, lineage, reporting, and stakeholder confidence.
+ Clearer understanding of marketing-sourced and marketing-influenced business impact.
+ Less manual reconciliation and reporting effort, with faster insight, planning, and optimization cycles.
+ An outcome-oriented product operating model with clear OKRs, prioritization, adoption, stakeholder alignment, and measurable business value.
About you
Basic qualifications:
+ 8+ years of Product Management experience, preferably with enterprise data, analytics, Marketing Technology, or business-to-business software as a service (B2B SaaS) products.
+ Deep understanding of Marketing business processes, campaign and demand-generation operations, performance management, and the relationship between Marketing activity and the sales and opportunity funnel.
+ Demonstrated experience with first-touch, last-touch, and multi-touch attribution; incrementality; experimentation; Media Mix Modeling; and marketing-sourced versus marketing-influenced reporting.
+ Strong technical product fluency in data modeling, identity resolution, event and campaign data, integrations, metadata, data quality, lineage, semantic definitions, and analytical architecture.
+ Working knowledge of anonymous, digital, and known identity patterns across advertising technology, marketing technology, customer data platforms, marketing automation, web analytics, CRM, and Sales Technology.
+ Proven ability to create a product vision and OKRs and translate them into roadmaps, epics, features, user stories, acceptance criteria, and prioritized backlogs.
+ Experience partnering with Data and Analytics, Data Science, Engineering, and Architecture teams to deliver trusted reporting and measurement products.
+ Ability to evaluate and apply industry standards and best practices rather than simply automate current processes.
+ Strong executive presence, facilitation, storytelling, and influence across Marketing, Sales, Finance, Data, and Technology.
Preferred qualifications:
+ Experience with Adobe Workfront or comparable planning and workflow platforms.
+ Experience with generative or agentic AI in analytics, decision support, or performance optimization.
+ Experience defining identity...
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