Thank you to Benu, Cass, and Ruchika for sharing your time and insights!

AI-generated Session Recap

Introduction and Panelist Introductions
‍Munish Gandhi from Statisfy introduced the webinar's focus on evaluating AI solutions for go-to-market teams, building business cases for CFOs, and discussing outcome data. Cass Ernst-Faletto from Pendo, Ruchika Chopra from Illumio, and Benu Aggarwal from Milestone introduced themselves, highlighting their experiences in revenue operations and leveraging AI to improve customer sentiment and organizational alignment.
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‍Statisfy's Success Metrics
‍Munish shared Statisfy's success metrics, including a 40% action rate on meeting insights, 85% accurate health scores, and significant productivity gains reported by customers like Observe. These metrics underscore the potential of AI to drive revenue growth, improve data collection, and enhance productivity.
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‍Evaluating AI at Pendo
‍Cass discussed Pendo's approach to evaluating AI, transitioning from a use-case-driven approach to embracing uncertainty and exploring the broader possibilities of AI. She emphasized the importance of demos, MVPs, and integrating AI with situational awareness through concepts like Model Context Protocol (MCP).
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‍Winning Over the CFO
‍Ruchika outlined a four-step process for building a compelling business case for AI solutions, focusing on understanding the audience (CFO), framing the problem with metrics, constructing a compelling narrative with ROI metrics, and presenting a clear execution plan. She highlighted the importance of stakeholder alignment, due diligence, and demonstrating a clear understanding of costs, returns, and implementation timelines.
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‍Milestone's AI Journey with Statisfy
‍Benu shared Milestone's journey with Statisfy, starting with Notetaker, which provided real-time insights and improved productivity. This led to replacing Gong, enabling organizational alignment, and measuring customer sentiment as a key metric. Benu emphasized the shift from lagging indicators to leading indicators, with AI helping to bring cross-functional teams together and focus on customer friction.
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‍Leading vs. Lagging Indicators
‍Benu explained the difference between lagging indicators (e.g., unpaid invoices) and leading indicators (e.g., customer dissatisfaction). Munish added that leading indicators include customers not achieving expected outcomes, which can be identified by benchmarking and combining data from various sources.