Real numbers from demand generation, marketing operations, and segmentation programs. Focus is always on tracked revenue impact, not vanity metrics.
Built and deployed a 7-cluster ML-driven segmentation model that increased email CTR by 85%+, reduced send volume by 17%, scaled the database 4x, and drove approximately $1.3M in incremental revenue. Earlier R-based work clustering 164K records produced $1.32M in tracked revenue through precision targeting.
Led a change management initiative that improved engagement metrics and opportunity volume across 23 business lines, delivering $1.23M in incremental revenue. Also raised lead conversion 23% and operational efficiency 19% through lead lifecycle redesign with Sales Operations.
Campaign analysis and landing page optimization lifted qualified lead capture by 11.2% and produced $373K in revenue.
Full MarTech audit and system optimization reduced customer acquisition costs 19% and lifted lead conversion 15%. Parallel work improved conversion rates 30% through lead scoring, multi-touch nurture, and CRM integration.
Reduced SMS opt-out rates from 65.9% to 8.2% (87.5% reduction) through behavioral analysis and a cross-channel re-engagement strategy, identifying $843K in retained LTV while scaling outbound volume.
Scaled HubSpot data infrastructure from 160K to 1.7M records, enabling sophisticated district-level B2B targeting, advanced segmentation, and personalized campaign orchestration. Also built an AI-powered multichannel executive dashboard unifying 12 data sources at zero vendor cost.
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