SELECT ACCOMPLISHMENTSCUSTOMER LIFETIME VALUE (CLV), PRODUCT MANAGEMENT, MACHINE LEARNING, & PREDICTIVE ANALYTICS Distribution channel lacked transparency to historical and predictive customer lifetime value (CLV) metrics. Develop business case, author business requirements, standardize business processes segregating value of B2B vs. B2C relationships, identify indicative data across 12 data sources, and partner with data science through feature engineering. Secure annual funding of $3M; democratize single source of truth for CLV; launch suite of predictive CLV models. INNOVATION, OPERATIONAL EXCELLENCE, COST-EFFECTIVE OUTCOMES AND SOLUTIONSReactive and non-scalable business processes drove increased costs and suboptimal analytics. Identify current state operational opportunities, perform market assessment of external data, complete process mapping and cross-reference tasks for structured / unstructured data sets, and orchestrate creation of new capability sourcing revelatory public data for new logo opportunities. Decrease forecast variation by 50% vs. naïve forecast; unlock 100x increase in process scalability.STRATEGIC THINKING, CROSS-FUNCTIONAL TEAM LEADERSHIP, & INCORPORATING BROADER BUSINESS CONTEXT Data collection gaps in sales processes and under investment in IT calcified organizational inertia to strategic opportunity. Conduct qualitative and quantitative market research, develop multi-dimensional views of internal benchmarks, identify and close data gaps, perform comparative analysis, and recommend strategies to inform pricing adjustments and bundled monetization opportunities. Develop new feedback loop informing GTM Strategy and relative pricing; establish regular forums with Sales, Pricing, and Leadership to drive behaviors and results.EXPERIMENTATION, REVENUE GROWTH, & MAPPING ALGORITHMIC SOLUTIONS TO BUSINESS METRIC IMPACTOut-dated, one-size-fits-all approach to prospect evaluation led to suboptimal cross company pricing. Conduct sensitivity analysis, develop business hypothesis, enhance customer lifetime value models, execute controlled A/B experiment to identify price elasticity of demand, perform performance analytics intersecting new segmentation data, and refine targeting protocols. Increased target sales 2-3x and market share ~1% annually; expected increase in income of $260M over 5 years.