Marketing Intelligence Systems

Context Brands across automotive, entertainment, and consumer categories needed deeper visibility into audience behavior, conversational patterns, buyer intent, and content performance across digital ecosystems. ⸻ Problem Traditional reporting structures often focused on surface-level engagement metrics while missing broader behavioral signals, category dynamics, customer intent, and market positioning opportunities. ⸻ Approach Led the development of marketing intelligence and social listening analysis frameworks combining: • conversational analysis • audience behavior • API-based data extraction • content benchmarking • category mapping • buyer intent analysis • cross-brand comparison Projects included: • Apple Music ES content intelligence • automotive buyer intent analysis • influencer performance evaluation • LATAM category research • content optimization frameworks Analysis systems were developed using: • API extraction workflows • R-based automation • cross-channel benchmarking • performance distribution analysis • qualitative + quantitative signal evaluation ⸻ Outcome The intelligence frameworks supported: • content optimization • audience segmentation • performance benchmarking • strategic media planning • buyer funnel alignment • influencer evaluation • cross-market analysis The systems also improved visibility into conversational behavior, performance distribution, and category-level audience trends across multiple LATAM markets.