Senior Director of Product Marketing

Job Responsibilities

1. 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.
      • In conjunction with PS and CS, leverage AI to flag advocacy indicators like successful renewals, go lives, etc. to trigger an advocacy conversation while sentiment is highest.
      • Create a dynamic curated reference library organized by vertical, use case, deal size, and buyer persona that is continuously maintained from signals and that validate the ROI framework. Leverage AI for case study production and to query and tag use cases.
      • Systematically connect satisfied customers with analysts and review sites.
      • Leverage Community as part of the intelligence loop but also the advocacy engine. AI monitors community forums and customer discussions to surface emerging themes, identify highly engaged members who are natural advocacy candidates, and flag champion conversations.
      • Drive pieces of the development and execution of GTM strategy/framework for all new products, features, and market expansions in conjunction with sales, partners and product. Define target segments, ICPs, pricing/packaging rationale, and channel strategy.
      • Partner with Product, Finance, and Sales to develop and evolve pricing and packaging strategies that reflect market value perception, competitive dynamics, and growth objectives derived from the intelligence loop.
      • Partner with sales and sales enablement to build WIN based assets, playbooks, battle cards, ROI frameworks, and objection-handling resources that directly shorten sales cycles and improve win rates. Leverage AI for content production, query, usage and continuous refresh.
      • Extend enablement programs to the partner ecosystem, ensuring channel and alliance partners can articulate Agiloft's value proposition and compete effectively in the field.
      4. Own Operationalizing for scale:
      • Build the AI Infrastructure for execution including AI stack tools (much of which already exist) and a centralized repository.
        • Get buy in from other team for data such as CRM data, product usage data, support tickets and NPS types of data
        • Cross-functional governance must be established via established cadences and RACIs
        • Determine with clarity and enforcement which functions of this role are done individually, through team members and through tools.
        • The intelligence engine needs both a consumption and publishing model:
          • Defined output formats for each audience
          • A defined channel for each output.
          • A feedback mechanism so recipients can signal what's useful and what’s not, self-improving the loop over time.
          5. Team Leadership & Organizational Development
          • Organize, develop, and retain a high-performing product marketing organization spanning core PMM, analyst relations, customer marketing, content strategy, Community, and communications. Define team structure, roles, and a clear career ladder.
          •  Foster a team culture defined by intellectual curiosity, customer obsession, data-driven decision-making and bold, clear communication.
          • Model and institutionalize strong working relationships with Product, Leadership, Sales, Partners and CS. Build the organizational habits and forums that keep company strategy and direction, GTM and product investment aligned and making informed decision quickly and with confidence.