Define and own the measurement framework for ZoomInfo’s PLG motion, including acquisition, activation, engagement, monetization, retention, and expansion
Establish the company’s source of truth for PLG performance, including KPI definitions, scorecards, executive reporting, and performance benchmarks
Define leading indicators that predict customer activation, product adoption, conversion, retention, and expansion outcomes
Ensure measurement consistency across products, teams, and business units, enabling a unified view of customer growth and product performance
Develop scalable frameworks that connect customer behavior to business outcomes and investment decisions
Own analytical understanding of the end-to-end customer journey, from acquisition and onboarding through monetization and long-term retention
Identify behavioral patterns, friction points, and conversion barriers that impact activation, adoption, retention, and expansion
Develop customer segmentation frameworks that reveal differences in growth outcomes across personas, customer segments, and product experiences
Lead investigations into significant changes in PLG performance, diagnosing root causes and quantifying business impact
Identify the behaviors and product experiences most strongly associated with successful customer outcomes and long-term value creation
Influence product investment and roadmap decisions by quantifying opportunity size, identifying high-leverage growth opportunities, and evaluating tradeoffs across competing initiatives
Serve as a strategic advisor to Product, Growth, and GTM leadership on customer behavior trends, adoption patterns, and monetization opportunities
Build analytical frameworks that help teams prioritize investments across onboarding, activation, engagement, monetization, retention, and expansion
Define measurement strategies for major product initiatives and ensure business impact is accurately assessed
Guide experimentation efforts across the PLG funnel, helping teams prioritize, evaluate, and scale growth opportunities
Deliver executive-level insights that inform product strategy, growth planning, and resource allocation
Redesign analytics workflows around AI-first operating principles rather than traditional manual processes
Build automated systems that continuously monitor product performance, surface anomalies, and identify growth opportunities at scale
Develop AI-assisted investigation workflows that accelerate root-cause analysis and reduce time-to-insight
Establish scalable reporting and monitoring infrastructure that minimizes manual effort while maintaining analytical rigor
Continuously evaluate emerging AI capabilities and incorporate them into the analytics operating model
Improve self-service analytics capabilities while maintaining governance, consistency, and trust in data