#68 Turning GTM data into insights - with Dan Schonfeld, VP, RevOps at Glia
Feb 17, 2025
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Dan Schonfeld, VP of Revenue Operations at Glia, dives into the transformative power of go-to-market data. He emphasizes the art of data storytelling to make analytics truly actionable. Listeners will learn about balancing strategic and operational analytics, as well as best practices for impactful Quarterly Business Reviews. Dan discusses how to effectively communicate insights to executives and explores the real vs. hype aspects of AI in analytics. His insights help build a strong, data-driven culture in revenue operations.
Data storytelling is crucial for RevOps leaders to transform analytics into actionable insights that drive executive decision-making.
Balancing operational efficiency with strategic insights is essential for RevOps teams to effectively communicate data implications and guide business strategies.
Deep dives
The Role of Revenue Operations in Data-Driven Decision Making
Revenue operations (RevOps) leaders emphasize the necessity of leveraging data for effective decision-making across organizations. Access to relevant analytics is critical, as it enables leaders to diagnose problems accurately and take appropriate actions. By understanding what is happening under the hood of the business, companies can orient their focus on key issues and improve their operational efficacy. This demonstrates that while organizations may claim to be data-driven, the execution and interpretation of these analytics can vary significantly.
Balancing Operational Efficiency and Strategic Insight
Success in revenue operations requires a delicate balance between operational efficiency and strategic insights. On the operational side, it is vital to create user-friendly tools and ensure information consistency, while strategic elements must focus on monitoring and interpreting key signals over time. Effective communication of insights is essential to ensure that all stakeholders, from sales to marketing, understand data implications and can make informed decisions. Thus, a robust strategy involves equipping teams with actionable insights that drive the overall business strategy.
The Importance of Data-Driven Storytelling
Data-driven storytelling is an underappreciated yet essential aspect of effective revenue operations. Beyond identifying trends, great RevOps leaders communicate the narrative behind the data, illustrating its significance to the business. Sharing insights with context—such as comparing new product win rates to historical data—allows for actionable strategies to emerge, guiding departments on how to scale successes. This emphasizes that the way insights are presented can significantly impact organizational alignment and strategic direction.
Best Practices for Quarterly Business Reviews
Quarterly business reviews (QBRs) serve as a vital platform for cross-functional communication, enabling teams to discuss performance, learnings, and future strategies. Effective QBRs involve preparing templates for leaders, presenting relevant metrics, and engaging in focused discussions on key insights. The success of these meetings relies on thoughtful preparation and the active involvement of essential stakeholders, creating a structured environment where actionable decisions can be made. Ultimately, the effectiveness of QBRs lies not only in the discussion but in the follow-up actions taken based on insights shared.
Danny Schonfeld, VP of Revenue Operations at GLIA, joins the podcast to break down how RevOps leaders can turn raw data into strategic narratives that drive executive decision-making. From QBRs to long-term planning, Danny shares his insights on making analytics actionable, building a strong data-driven culture, and ensuring that RevOps is seen as a strategic function rather than just a reporting team.
We cover:
Why data storytelling is the key to making analytics actionable
How RevOps teams can balance operational and strategic analytics
Best practices for preparing and running effective QBRs
How to communicate insights to executives in a meaningful way
The role of AI in analytics—what works and what doesn’t (yet)
How to build demand for RevOps analytics by showcasing impact