What does it really mean to be data-driven? Mark Gergess, VP of Data and BI at DoubleVerify, joins the show to unpack how data teams can go beyond dashboards to drive meaningful business action. From building an internal consulting lens to evaluating the latest AI tools, Mark shares how his team translates complex data flows into measurable revenue impact. If you’ve ever wrestled with the gap between insights and outcomes, this conversation will hit home.
Key Takeaways
• Being data-driven is about driving action, not just reporting numbers
• Stakeholders don’t care about your data problems—they care about business outcomes
• The biggest challenge with AI adoption isn’t the model, it’s the use cases
• Efficiency gains from AI should shift focus from ETL tasks to solving real business problems
• Data culture health is measured by how naturally teams rely on data day-to-day
Timestamped Highlights
01:17 How DoubleVerify helps advertisers build safer, more effective digital campaigns
04:55 Why the definition of “data-driven” still varies and why it matters
09:25 Measuring whether data efforts are moving the needle on revenue
13:15 How to separate hype from value when evaluating AI and GenAI tools
17:10 Lessons from the data science boom and why companies must go “all in” with AI
25:31 Can AI act as your junior analyst? Where efficiency gains really show up
27:01 How freeing up time changes the structure of data teams and boosts business impact
A thought worth holding onto
“It’s not about dashboards. It’s not about reporting. It’s about doing something with the information.”
Pro Tips
Mark recommends treating AI as a “junior analyst”—let it handle quick, lower-priority questions so your team can focus on bigger business challenges.
Call to Action
Enjoyed the conversation? Share this episode with a colleague who talks about being “data-driven.” Subscribe on your favorite podcast platform and connect with me on LinkedIn for more insights from leaders shaping the future of data and technology.
