Josh Weil - Florida Progressive Democrat US Inactive
JOSH WEIL FOR CONGRESS
Flip this seat >>
Ad copy
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)
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 55.1/100 |
| Spend / Reach / Long. / Eff. | 63.0 · 92.5 · 6.9 · 57.9 |
| Spend range | USD 15,000–19,999 |
| Impressions | 450,000 – 499,999 |
| CPM (≈ $/1k impr) | USD 36.84 |
| Est. audience size | — |
| Days live | 26 (2025-02-24 → 2025-03-22) |
| Created | 2025-02-24 |
| 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 | urgency |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Relatable everyman framing — 'single dad, teacher' identity baked directly into the video subtitle overlay |
| Tactic | The ad uses contrast fundraising, pairing a sympathetic underdog self-introduction with urgent anti-MAGA framing to drive small-dollar national donations against a named extremist opponent. |
Where it ran (delivery by region)
| Florida | 15.8% |
| California | 12.3% |
| New York | 7.9% |
| Massachusetts | 4.6% |
| Washington | 3.8% |
| Illinois | 3.7% |
| Texas | 3.4% |
Who saw it (delivery)
| 18-24 · female | 0.8% |
| 45-54 · male | 5.1% |
| 65+ · male | 9.5% |
| 65+ · female | 23.8% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 6.5% |
| 55-64 · female | 16.2% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 12.0% |
| 18-24 · male | 0.9% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 5.2% |
| 35-44 · female | 10.5% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 3.5% |
| 25-34 · female | 4.7% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.4% |
