Josh Weil - Florida Progressive Democrat US Inactive
JOSH WEIL FOR CONGRESS
Let's flip Congress
Ad copy
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. On April 1st we can FLIP Congress and put a stop to Trump and Project 2025. I'm Josh Weil, a public educator and Democratic nominee for the April 1st special election in Florida's 6th Congressional District. 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)
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 47.1/100 |
| Spend / Reach / Long. / Eff. | 49.0 · 80.0 · 0.8 · 58.4 |
| Spend range | USD 4,500–4,999 |
| Impressions | 125,000 – 149,999 |
| CPM (≈ $/1k impr) | USD 34.54 |
| Est. audience size | — |
| Days live | 4 (2025-03-14 → 2025-03-18) |
| Created | 2025-03-14 |
| 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 | contrast comparison |
| Message type | fundraising |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | opponent's inflammatory attack quote displayed as the video subtitle, reclaimed as a fundraising hook |
| Tactic | The ad uses inoculation strategy — surfacing the opponent's smear attack quote to generate donor outrage and urgency around the special election. |
Where it ran (delivery by region)
| Florida | 11.6% |
| California | 11.4% |
| New York | 6.7% |
| Washington | 4.6% |
| Massachusetts | 4.5% |
| Pennsylvania | 3.9% |
| Texas | 3.7% |
Who saw it (delivery)
| 18-24 · female | 0.1% |
| 45-54 · male | 4.9% |
| 65+ · male | 21.0% |
| 65+ · female | 34.3% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 10.4% |
| 55-64 · female | 14.1% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 5.9% |
| 18-24 · male | 0.1% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 2.9% |
| 35-44 · female | 2.8% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 1.0% |
| 25-34 · female | 0.9% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.8% |
