Josh Weil - Florida Progressive Democrat US Inactive
JOSH WEIL FOR CONGRESS
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Ad copy
This race is COMPETITIVE. We're neck-and-neck in the early voting, and we need all hands on deck to FLIP this seat on April 1st and deliver a huge blow to Trump's agenda in Congress. I'm Josh Weil, a public educator and Democratic nominee for the April 1st special election in Florida's 6th Congressional District. I'm running against Trump and DeSantis' hand-picked nominee, Randy Fine. He's an ultra-MAGA extremist who will be a rubber stamp on everything they want to do in Congress. To stop him, we need every Democrat in the country to pitch in and help. Please donate today, and with your support we can flip this seat and take the wind out of Trump's MAGA movement. Josh Weil Democrat for U.S. Congress (FL-6)
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Performance proxies
| Overall score | 48.7/100 |
| Spend / Reach / Long. / Eff. | 53.9 · 83.1 · 0.3 · 57.3 |
| Spend range | USD 7,000–7,999 |
| Impressions | 175,000 – 199,999 |
| CPM (≈ $/1k impr) | USD 40.0 |
| Est. audience size | 100 – 1,000 |
| Days live | 2 (2025-03-19 → 2025-03-21) |
| Created | 2025-03-19 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | FL — Joshua Weil |
| Surfaced by | “senate:Joshua Weil” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | none |
| Call to action | donate |
| Standout element | Torn-paper Daytona Beach News-Journal clipping showing vote-by-mail competitiveness stats as social proof |
| Tactic | Uses a credible local newspaper excerpt to validate the 'neck-and-neck' urgency claim, converting third-party validation into a fundraising trigger. |
Where it ran (delivery by region)
| California | 15.2% |
| Florida | 12.0% |
| New York | 6.5% |
| Washington | 5.8% |
| Massachusetts | 4.0% |
| Illinois | 4.0% |
| Texas | 3.5% |
Who saw it (delivery)
| 18-24 · female | 0.3% |
| 45-54 · male | 5.2% |
| 65+ · male | 14.1% |
| 65+ · female | 28.0% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 7.9% |
| 55-64 · female | 15.3% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 9.0% |
| 18-24 · male | 0.4% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 5.2% |
| 35-44 · female | 7.4% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 2.7% |
| 25-34 · female | 3.0% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.6% |
