It’s a festive Destination Discourse that turns into a full-on industry thought exercise. Stuart Butler and Adam Stoker welcome back Emily Zertuche (record-setting past guest) for a Christmas episode that starts with meta-glasses and “Stu’s News” lyrics finally appearing on YouTube… then quickly escalates into a serious conversation about “data hangovers,” measurement overload, and why DMOs struggle to answer the simplest question in the boardroom: Did it work?

Emily argues the problem isn’t a lack of data. It’s a lack of narrative coherence and governance across an increasingly messy data stack. She introduces the “whiskey and Coke test” for communication: boards don’t want an over-sweetened cocktail of metrics, they want a simple, defensible truth. The group debates attribution, false precision, and how AI will soon act like a prosecutor cross-examining discrepancies across dashboards and vendor reports.

Then Emily goes for the sacred cow: she says the marketing funnel is a foundational conceptual error for destination marketing because vacations don’t behave like checkout flows. Travel decisions are messy, probabilistic, and shaped by circumstance. That pushes the conversation toward counterfactuals (“what if we did nothing?”), humility, and ranges instead of single ROI numbers.

They wrap by calling it an existential issue for the industry, and invite more people into the conversation. Emily’s homework: go figure it out and come back in early January.

⸻

What you’ll hear in this episode
• A chaotic Christmas intro, eggnog energy, and the debut of Stu’s News lyrics on YouTube (because Stuart didn’t realize Zoom exports could include screen share).
• Meta glasses talk: capturing content hands-free, plus the “creepy” reality of audio + AI + ad targeting.
• Stu’s News topic: Thailand’s “Half and Half” domestic travel subsidy and the idea of governments paying people to travel, plus discussion of whether incentives could ever apply to leisure travel.
• Emily’s big thesis: DMOs have a “data hangover” from too many tools, dashboards, vendors, and definitions.
• The boardroom moment of truth: “Did it work?” and why it’s so hard to answer coherently.
• Emily’s framing: this is not just a data problem, it’s a meaning problem and a narrative problem.
• The “whiskey and Coke test”: if you can’t explain the system simply, it loses legitimacy.
• Funnel vs field: vacations behave like weather and probability, not a linear cause-and-effect funnel.
• Counterfactuals and incrementality: what would have happened without the spend?
• The danger of false precision (single ROI numbers) vs the honesty of ranges and assumptions.
• The AI warning: stakeholders will use tools like ChatGPT/Gemini to find discrepancies and expose narrative-first reporting.
• The prescription: govern the data stack (vendor layer → modeling layer → narrative layer) so the story is coherent, honest, and defensible.

⸻

Key quotes and concepts (verbatim from the transcript)
• “Data hangover.”
• “Did it work?”
• “Measurement capacity has outrun our narrative coherence.”
• “If a system can’t explain itself simply… it will eventually lose legitimacy.” (the “whiskey and Coke test” idea)
• “False precision is so much more dangerous than uncertainty, because it’s a lie!”
• “We’re not here to sell a number, we’re here to sell the logic that produced the number.”
• Funnel critique: travel decisions are “spaghetti” (and even “spaghetti with maple syrup”).
• Counterfactual framing: the honest question is “What if we did nothing?”
• AI as prosecutor: it will cross-examine discrepancies across reports and dashboards.

⸻

Listener takeaways
• If you can’t answer “Did it work?” in a way a board member can repeat, your measurement system is a risk—not an asset.
• You don’t need more dashboards. You need governance and a narrative hierarchy that explains assumptions and uncertainty.
• Stop treating destination decisions like e-commerce conversions. Travel influence is probabilistic and delayed.
• If your reporting relies on cherry-picked metrics or “real data” claims, assume AI will expose it soon.
• Credibility comes from assumptions + logic + ranges, not one magic ROI number.