Sustained Media Execution
Spokesperson Campaign + Interview Prep
Prediction Markets Spokesperson Campaign
Client and spokesperson names have been removed per NDA. The strategy, structure, and substance are unchanged from the original working documents.
This sample is from a sustained media campaign I ran for the managing partner of a crypto venture fund. The goal was to establish him as the go-to voice on prediction markets, a space where the fund had direct portfolio exposure to underlying infrastructure.
Rather than a single pitch, I built a core framework around the spokesperson and continuously updated it as the news cycle shifted: the Super Bowl became a market integrity story, midterm primaries became a polling vs. markets story, and so on. Every time prediction markets hit the news, we had a ready-to-send pitch tailored to the moment. When interviews were booked, I prepared detailed briefing documents like the one below to ensure the spokesperson was prepped for the specific reporter, outlet, and angle.
This approach resulted in interviews with Bloomberg, The New York Times, and other Tier 1 outlets.
Campaign Timeline: How the Pitch Evolved
The core pitch framework was built once and updated as the news cycle created new entry points. Each version kept the same spokesperson and the same core thesis, but reframed the hook to match the moment:
Version 1
Sports betting is eating prediction markets
The original hook. The fund had published research showing 75% of all prediction market volume now came from sports betting, with NFL, UFC, and Premier League leading. Pitched the spokesperson on why this convergence between gambling, finance, and forecasting matters, and what it means for platforms like DraftKings and FanDuel.
Version 2
CBS News newsjack
CBS News ran a Sunday Morning segment framing prediction markets as the next phase of online gambling. Quickly reframed the pitch around what the mainstream coverage was missing: the financialization of forecasting, and why crypto is quietly building the primitives for a parallel, retail-native derivatives market.
Version 3
Regulatory battle
A prediction market platform squared off against Connecticut regulators in federal court over sports event contracts. Reframed around the jurisdictional fight: the CFTC classifying these as commodities under federal regulation vs. 31 states with their own online gambling licenses. Pitched the spokesperson on why this battle could end up at the Supreme Court.
Version 4
Super Bowl integrity test
As platforms rolled out institutional-grade surveillance ahead of the Super Bowl, reframed around market integrity and manipulation detection. The hook shifted from "these markets are interesting" to "this is the stress test that determines if they're legitimate."
Version 5
Midterm primaries (print)
As 2026 midterm primaries approached, repositioned for print reporters. Angle: elections are no longer just political events but data stress-tests. Prediction markets are becoming the primary signal, not just an alternative.
Version 6
Midterm primaries (broadcast)
Same news hook, rewritten for broadcast producers. Shorter, punchier subject line ("The Polls Are Broken"), emphasis on spokesperson availability for live hits on short notice.
Follow-ups
Ongoing reporter relationship management
Targeted follow-ups accompanied each version, reframing the spokesperson as a source for ongoing commentary rather than a one-time quote. Each follow-up was tailored to the specific reporter and adjusted the angle based on what was moving in the news that week.
Below is the briefing document prepared for the resulting New York Times interview.
Executive Press Briefing: The New York Times
1. Outlet and Reporter Context
The New York Times will treat prediction markets as an economics and incentives story, not a niche trading trend. The angle is likely to focus on what these markets reveal about trust, institutions, regulation, and how people make decisions under uncertainty.
The reporter is an American economy reporter who often pressures claims through:
- "What's actually new here?"
- "What's the incentive structure?"
- "Who benefits and who gets harmed?"
- "What does this say about the economy and institutional trust?"
2. How to Frame the Conversation
Goal: Make prediction markets feel like an economics story, not a crypto story.
Anchor on
- Prediction markets as information markets that convert beliefs into prices
- Their rise as a sign of demand for alternative signals in an uncertain environment
- Why they're compelling: incentives + constant updating + fast feedback loops
- The real debate: useful signal vs. hype vs. manipulation risk vs. legitimacy
Tone to aim for: Calm, analytical, non-partisan, and non-hypey.
3. Key Talking Points
What prediction markets are (plain English)
- Markets where people trade on outcomes (economic releases, policy decisions, major events)
- Prices act like implied probability (not certainty)
- Best understood as a signal: "what people are willing to back"
Why they're getting attention now
- People want signals that update faster than slow polling cycles and expert commentary
- A cultural shift toward quantifying uncertainty, not just debating opinions
- Wider normalization of "put your money where your mouth is" behavior
What they do well (at their best)
- They can update quickly as new information arrives
- They aggregate viewpoints into a single number
- They impose accountability: it's not just a take, it's a priced belief
Where they break down
- Thin markets can be noisy and easier to push around
- Prices can reflect herd behavior, hype, and attention dynamics
- The biggest mistake is treating the price as "truth" instead of a messy indicator
The responsible way to talk about them
- Use as one input, not the input
- Focus on why probabilities move, not just the number
- Treat the signal with skepticism: liquidity, participation, and incentives matter
4. Likely Questions and Suggested Framing
Q: What's actually new about prediction markets right now?
- The scale of attention and how mainstream the conversation has become
- Better tooling and easier access has compressed the feedback loop
- They're increasingly being used as a real-time signal, not just a novelty
Q: Should we take these markets seriously as information tools?
- They can be useful, but only with context
- They're best at showing directional movement and shifting consensus, not certainty
- The signal quality depends on liquidity, participation, and market design
Q: Are prediction markets "better than polls" or is that overstated?
- It's overstated if framed as a universal rule
- Polls measure snapshots of opinion; markets measure priced expectations
- The most useful thing is often how the probability changes, not the exact number
Q: What's the biggest misconception when people look at prediction market odds?
- Confusing "probability" with "truth"
- Treating a market price as inevitability
- Ignoring the mechanics: liquidity, incentives, and who's participating
Q: How vulnerable are these markets to manipulation or coordinated activity?
- Vulnerability is highest in thin markets with low liquidity
- Even when prices get pushed, it can create opportunities for others to trade against it
- The real risk is people amplifying a noisy price as a definitive signal
Q: Do prediction markets create perverse incentives by turning important outcomes into a betting product?
- That risk exists, especially if they're treated like entertainment content
- The counterpoint is they can encourage probabilistic thinking over certainty
- The impact comes down to platform design and how media and the public use them
Q: Where do regulators fit into all of this?
- These products sit at the intersection of consumer protection, markets, and public interest
- Legitimacy matters because trust in the integrity of the market is the whole value proposition
- Clear rules are important so "information tools" don't become purely extractive gambling products
Q: How should journalists responsibly reference prediction markets?
- Treat them like polls or forecasts: informative, but not definitive
- Focus on movement over time, not one number
- Add context: liquidity, volume, and what new information may be driving changes
- Avoid framing that implies inevitability or endorsement
5. Reminders for Strong, Quotable Answers
- Focus on the macro significance rather than platform-by-platform features
- Use concrete examples (elections, CPI releases, AI benchmarks)
- Highlight crypto's role in pioneering the primitives now being adopted by mainstream markets
- A forward-looking point on forecasting becoming financialized will resonate with economics and business reporters
6. Topics to Avoid and How to Pivot
If the conversation moves toward any of the following, redirect back to the macro story:
Specific portfolio company details or fund performance
Pivot to: "What I can speak to is the broader infrastructure trend we're seeing across the space."
Price speculation on any token or platform
Pivot to: "The more interesting question is what these markets tell us about how people process information, not where prices go."
Regulatory predictions or policy advocacy
Pivot to: "I think the right framing is what kind of rules would make these markets most useful as information tools."
Competitor criticism or naming specific platforms negatively
Pivot to: "The market is still early enough that the bigger question is whether the category earns trust, not which platform wins."
Gambling framing
Pivot to: "The distinction matters. These are information markets. The value is in what the prices tell you, not in the wagering itself."