AI Marketing Intelligence SaaS - a unified system that analyzes external digital signals and internal data - from Social & AI Listening to Conversational Intelligence, Reviews, Content, and internally owned databases - transforming scattered data into actionable, decision-ready intelligence. Hapttic goes beyond traditional marketing analytics and social listening by analyzing context, intent, and meaning, not just metrics or mentions. What makes Hapttic different? Most tools focus on one data type or one channel. Hapttic connects everything into one intelligence system. It brings together: -Public digital signals -Internally owned data -AI-driven interpretation -Strategic insights & recommendations All in one platform. Hapttic Marketing Intelligence Suite Hapttic’s suite is designed to cover the entire marketing intelligence layer: > Social Listening Monitors brand mentions and conversations across social platforms — turning online discussions into structured intelligence. > AI Listening Tracks how brands, topics, and competitors appear inside AI-generated responses (ChatGPT, Gemini, Claude, etc.), analyzing visibility, framing, and narrative control in AI environments. > Conversational Intelligence Analyzes inboxes, messages, comments, and customer conversations to uncover intent, pain points, and recurring patterns. > Review Analysis Processes reviews across platforms to detect sentiment drivers, experience gaps, and reputation risks. > Content Analysis Evaluates owned and competitor content to understand messaging effectiveness, narrative alignment, and topic performance. > Internal Data Analytics Analyzes internally owned databases (CRM, support data, operational inputs) and connects them with external signals for full-context insights. What Hapttic enables • From dashboards to decisions AI-powered insights instead of static reporting. • One source of truth Marketing, PR, content, customer teams, and leadership work from the same intelligence layer. • Early signal detection Identify trends, risks, and opportunities before they scale. • Context over volume Understand why something is happening, not just how often. • AI embedded at every layer From data collection to interpretation, insight generation, and recommendations.