Responsibilities

• Market Intelligence – Establish a systematic, high quality, always-on intelligence engine by deploying AI powered monitoring tools across all market sources including, but not limited to, competitor messaging, product announcements and pricing shifts, analyst commentary and buyer sentiment across review sites, social channels, and press.
• Use AI transcription to process customer interviews, Customer Advisory Board sessions, win/loss calls, customer assets, sales call recordings, and deal profiles at scale.
• Operationalize the intelligence engine for decision making. Leverage AI to generate content and rank signals from the intelligence engine to be delivered in a consistent cadence. Further operationalize a closed feedback loop where product and sales decisioning is measured and tracked for impact.
• Partner with Customer Support and Product to leverage AI for sentiment analysis, identifying patterns across customer responses, support tickets, and community forums to surface customer pain points, usage and consumption issues and behavioral patterns.
• 2. Product Strategy/Influence – Serve as an embedded partner to product leadership by bringing validated market demand, buyer and customer intelligence and competitive context into roadmap prioritization decisions. Via the intelligence engine, ensure product prioritization and investment is consistently tied to demonstrable market opportunity.
• Leverage the AI intelligence engine specifically to cluster, prioritize feature requests and pain points into ranked themes that inform roadmap conversations with evidence.
• Champion and drive a post-launch mindset in collaboration with Product/GTM/CS. Define how customers should consume, adopt and expand usage of each solution by use case.
• In partnership with product, develop and maintain a clear, compelling use case library where appropriate by buyer persona, industry vertical, and deployment scenario. Must leverage AI to:
• monitor customer usage patterns, win/loss data, and market signals to automatically recommend use cases in or out.
• identify emerging use cases that customers are creating themselves though patterns of product usage that don't match any documented use case. This prioritizes Product and GTM investment.
• Personalize adoption suggestions at scale surfacing the right use case content to the right customers at the right time via multiple outlets.
• Orchestrate high-impact, cross-functional product launches that drive measurable market awareness, pipeline generation, and customer adoption.
• Contribute to the measurement framework for product launches and releases. This is a partnership with product that looks beyond just tactical execution metrics into usage, consumption, customer behavior changes and revenue contribution.
• 3. Own our win strategy for GTM – Leverage the intelligence loop to rapidly derive our “WIN” messaging frameworks, positioning hierarchies, and persona-specific narratives.
• Use AI-assisted testing to evaluate messaging resonance, identify highest performing narrative and positioning.
• Ensure every external-facing message is aligned, differentiated, and resonant with the economic and functional buyers we serve, addresses use cases and drives consumption.
• Drive the externalization of Agiloft's economic value framework by leveraging AI to produce evidence-based frameworks/assets/justification for prospects to establish compelling internal business cases investment.
• Create thought leadership. Leverage the AI intelligence loop to own, create and disseminate our point of view on the future of CLM and Contracts AI . This is a distinct and ideally disruptive position, based on evidence, that positions where the categories are heading and Agiloft as a category leader in both.
• Ignite our advocacy engine.
• Leverage AI to continuously score accounts against usage data, NPS signals, support sentiment, and engagement patterns to surface the customers most likely to advocate.