Teams at HighLevel

Owns company-wide revenue retention and add-on monetization analytics across CPaaS, AI features, Customer Success, and Finance. Builds canonical GRR, NRR, churn, and monetization metrics; applies causal inference methods to distinguish true retention drivers from bias and data artifacts; guides experimentation and forecasting; and influences cross-functional product, pricing, lifecycle, and customer success decisions without direct authority.

Owns customer growth analytics across onboarding, activation, trial-to-paid, multi-product adoption, retention, and expansion. The role develops canonical metrics, segment definitions, value models, and causal-inference standards; identifies behaviors that predict expansion; evaluates experiments; and translates product, behavioral, and revenue data into guidance for Growth, GTM, Finance, and product leaders. It also shapes event taxonomy, influences roadmap and investment decisions, and establishes reusable analytical practices across teams.

Own analytics and measurement for HighLevel’s AI product portfolio. Define instrumentation standards, feature-level KPIs, adoption and quality metrics, and rigorous approaches for evaluating nondeterministic AI features. Partner with experimentation leaders, PMs, engineering, and Analytics Engineering to close data gaps, influence product roadmaps, establish canonical metrics, and mentor future analysts.