What’s the biggest lie marketers tell themselves about their own data?
- Part 1Why Marketers Should Treat AI Like a Frenemy
- Part 2The best data source to understand what is popular in B2B media
- Part 3What is your automaton tech-stack?
- Part 4What is the coolest agent you’ve built for yourself?
- Part 5 What’s the biggest lie marketers tell themselves about their own data?
Episode Chapters
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00:29: Building AI Agents for Networking
A location-based agent automatically identifies relevant contacts to reach out to in upcoming travel cities based on relationship strength and relevance.
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01:13: Video Performance Analysis Tool
An AI agent analyzes video content frame by frame, mapping visual elements like cuts, shots, and animation against performance data to identify what drives viewer engagement.
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01:54: What Keeps Viewers Engaged
Visual and written hooks in the first few seconds matter, but continuous re-hooking throughout content prevents viewers from dropping off or switching away.
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02:53: The Thumbnail Team Standard
Top brands like Mr. Beast and Red Bull employ entire teams dedicated solely to creating thumbnails, setting the competitive bar for visual attention-grabbing.
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Episode Summary
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What's the Biggest Lie Marketers Tell Themselves About Their Own Data?
Introduction
Charlie Gri ell, Co-CEO of RightMetric, challenges the conventional wisdom that first-party data is all marketers need for success. With experience leading marketing at Red Bull and Aritzia, Gri ell brings a unique perspective on why relying solely on owned data is "like driving while staring in the rearview mirror." His strategic research firm helps brands like Meta, Red Bull, and lululemon decode what audiences actually do online by leveraging external data signals that most marketers overlook. -
The AI Agent Revolution in Marketing
Gri ell reveals how AI agents are transforming both personal productivity and marketing analytics. His personal networking agent automatically identifies relevant contacts in cities he's traveling to, sending recommendations based on relationship strength and relevance without any manual input. This automation demonstrates how AI can handle complex, context-aware tasks that previously required significant human effort and memory. -
Video Performance Analysis at Scale
RightMetric's video analyzer agent represents a breakthrough in content optimization. The tool watches videos frame by frame, identifying whether content is live-action or animated, tracking cut patterns, and distinguishing between product close-ups and wide shots. By mapping these visual elements to performance data, the agent pinpoints exactly where viewers drop off or stay engaged, providing actionable insights that human analysts would struggle to capture at scale. -
The Science of Keeping Viewers Engaged
When pressed about what actually keeps viewers watching, Gri ell emphasizes that success goes beyond simple tricks. "The first frame matters, the first one to two seconds matter. But then how are you continuing to rehook people?" he explains. Modern viewers are constantly looking for reasons to swipe away, making continuous engagement critical throughout the entire content experience. -
Visual Hooks and the Attention Economy
The sophistication required to compete in today's content landscape is staggering. Gri ell points out that Mr. Beast and Red Bull don't just have thumbnail designers—they have entire thumbnail teams. This level of investment in visual hooks demonstrates the competitive reality marketers face when trying to capture and maintain audience attention against world-class content creators. -
Beyond First-Party Data Limitations
The biggest lie marketers tell themselves is that their own data tells the complete story. RightMetric's approach combines external data signals from platforms like Tubular with AI analysis to reveal patterns invisible in first-party analytics. This outside-in perspective helps brands understand not just how their content performs, but why it performs that way compared to competitors and what opportunities exist in the market. -
Conclusion
Gri ell's insights reveal a fundamental shift in how marketers should approach both AI and data strategy. Rather than viewing AI as a threat or relying solely on internal metrics, successful marketers will treat AI as a powerful ally for uncovering external insights and automating complex analytical tasks. The key is recognizing that great strategy starts where your owned data stops, and using AI to bridge that gap with sophisticated analysis of the broader competitive landscape. -
- Part 1Why Marketers Should Treat AI Like a Frenemy
- Part 2The best data source to understand what is popular in B2B media
- Part 3What is your automaton tech-stack?
- Part 4What is the coolest agent you’ve built for yourself?
- Part 5 What’s the biggest lie marketers tell themselves about their own data?
Up Next:
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Part 1Why Marketers Should Treat AI Like a Frenemy
AI reliability challenges plague over half of marketers despite vendor promises of perfect insights. Charlie Grinnell is Co-CEO of RightMetric, a strategic research firm specializing in external data intelligence for competitive advantage. The discussion covers treating AI as a "frenemy" that requires human oversight, building automation workflows through iterative prompt refinement, and combining internal analytics with external market signals for strategic context.
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Part 2The best data source to understand what is popular in B2B media
Marketers struggle with AI reliability and accuracy. Charlie Grinnell is Co-CEO of RightMetric, a strategic research firm specializing in external data intelligence for competitive marketing insights. The discussion covers treating AI as a "frenemy" that requires structured data inputs, building automation workflows through iterative testing, and validating AI outputs by asking it to explain its reasoning process.
Play Podcast -
Part 3What is your automaton tech-stack?
Marketers struggle to build effective AI automation stacks that actually drive results. Charlie Grinnell, Co-CEO of RightMetric, explains how external data transforms AI accuracy and marketing strategy. The conversation covers building custom agents for networking automation, developing video analysis tools that map viewer engagement frame-by-frame, and creating visual hooks that compete with brands like MrBeast and Red Bull.
Play Podcast -
Part 4What is the coolest agent you’ve built for yourself?
Marketers struggle with AI reliability and accuracy. Charlie Grinnell is Co-CEO of RightMetric, a strategic research firm specializing in external data intelligence for brands like Meta and Red Bull. He discusses building AI agents that automatically identify networking opportunities based on calendar events, creating video analysis tools that map viewer engagement to specific visual elements, and developing workflows that combine internal performance data with external market signals to reveal competitive blind spots marketers miss when relying solely on first-party dashboards.
Play Podcast -
Part 5What’s the biggest lie marketers tell themselves about their own data?
Marketers rely too heavily on first-party data for AI strategy. Charlie Grinnell is Co-CEO of RightMetric, a strategic research firm specializing in external data intelligence for brands like Meta and Red Bull. His team built a video analyzer that maps frame-by-frame content against performance data to identify what keeps viewers engaged. The discussion covers automated networking agents and the critical importance of visual hooks in the first seconds of video content.