  Online marketing faces formidable challenges in managing and interpreting
immense volumes of data necessary for competitor analysis, content research,
and strategic branding. It is impossible to review hundreds to thousands of
transient online content items by hand, and partial analysis often leads to
suboptimal outcomes and poorly performing campaigns. We introduce an
explainable AI framework SoMonitor that aims to synergize human intuition with
AI-based efficiency, helping marketers across all stages of the marketing
funnel, from strategic planning to content creation and campaign execution.
SoMonitor incorporates a CTR prediction and ranking model for advertising
content and uses large language models (LLMs) to process high-performing
competitor content, identifying core content pillars such as target audiences,
customer needs, and product features. These pillars are then organized into
broader categories, including communication themes and targeted customer
personas. By integrating these insights with data from the brand's own
advertising campaigns, SoMonitor constructs a narrative for addressing new
customer personas and simultaneously generates detailed content briefs in the
form of user stories that can be directly applied by marketing teams to
streamline content production and campaign execution. The adoption of SoMonitor
in daily operations allows digital marketers to quickly parse through extensive
datasets, offering actionable insights that significantly enhance campaign
effectiveness and overall job satisfaction
