• Owns HubSpot CRM structure, hygiene, and governance • Designs and implements AI-driven automations across GTM and customer success workflows • Builds and maintains data pipelines across CRM, product, and marketing systems • Develops dashboards that turn raw data into actionable insight • Success means a cleaner, more automated, and more reliable revenue engine that scales with the business

• Build and maintain dashboards and reports across the sales funnel (MQL → SQL → Opportunity → Closed Won) • Diagnose and solve revenue challenges using data—understand why conversion drops at specific stages, how compensation changes impact velocity, what drives forecast misses • Proactively surface revenue insights (not just respond to asks) "Here's a pipeline coverage problem emerging and here's how to fix it" • Deliver monthly revenue insights and strategic recommendations to Sales, Marketing, and Success leadership • Own the forecasting workflow end-to-end: design the process, support monthly forecasting cycles, conduct variance analysis (forecast vs. actuals) • Identify why forecasts miss and recommend improvements to increase accuracy (90%+ target) • Support board reporting and executive-level forecasting conversations • Audit CRM regularly to identify data quality issues and gaps • Document data standards and best practices; train Sales and Marketing teams on proper CRM usage • Build HubSpot workflows and automation to prevent bad data from entering the system • Drive adoption of data hygiene practices cross-functionally • Document and standardize sales processes (qualification criteria, pipeline stages, deal progression) • Identify inefficiencies in the revenue lifecycle and recommend improvements • Track compensation model impact on sales performance and outcomes • Own HubSpot configuration and optimization (custom properties, lifecycle stages, workflows, automation, integrations) • Partner with leadership on systems improvements and tooling decisions

• Structure segmentation and clustering of the customer base; • Define performance, propensity, profitability and risk cohorts; • Create commercial and financial prioritization models; • Develop lifecycle strategy for the customer portfolio; • Identify levers to grow TPV (Total Payment Volume) and receivables cession; • Define monetization strategies by customer profile; • Maximize LTV and customer retention; • Build profitability models by customer and cohort; • Direct commercial activity priorities; • Define appropriate offers for each customer profile; • Build activation, retention and win-back (recovery) campaigns; • Integrate commercial and financial intelligence; • Turn transactional data into operational strategy; • Develop performance indicators for the ecosystem; • Identify expansion and monetization opportunities; • Establish an analytical view of the financial value chain.

• Serve as the owner of monitoring and governance for key Customer Success metrics, ensuring conceptual consistency and reliability in measures such as churn rate, early churn, NRR/NDR, retention metrics, time-to-first-value, ongoing metrics, usage metrics, health score, stickiness, adoption metrics, and others. • Maintain regular tracking of the department’s metrics and provide strategic insights to company leadership on drivers behind metric fluctuations. • Support the planning and evolution of Customer Success metrics, contributing to the definition, review, and standardization of indicators that accurately reflect customer base health and the impact of CS initiatives. • Prepare executive reports that summarize the main results and trends of the Customer Success operation. • Recommend improvements and adjustments to the customer journey based on market best practices and data. • Create and deliver performance presentations for leadership and partner teams, translating data and metrics into clear, action-oriented narratives that highlight risks, opportunities, and recommendations. • Support the planning, definition, and evolution of Customer Success KPIs, ensuring consistency and correct interpretation of the area’s metrics. • Work closely with Customer Success, Support, Product, Revenue Operations, BI and other company teams to ensure alignment in the interpretation and use of metrics. • Support Customer Success leaders and teams in reading and leveraging performance indicators, helping to drive more data-informed decisions in account management.