Hector Mujica for Florida
DONATE TO DEFEAT MOODY >>>
We have the message. Now, we just need the airtime. The only problem is TV time in Florida is incredibly expensive and powerful stories only matter if people see them. Ashley Moody is sitting on a massive war chest funded by corporate lobbyists and MAGA special interests who want to keep things exactly the way they are. If we don't get this ad on the air, and keep it there, Moody’s special-interest millions will drown out the truth. We can’t let that happen if we want to win this Senate seat. Our team is preparing a major statewide TV and digital ad buy, but we need an immediate surge of grassroots donations to make it happen. Chip in $10, $25, or whatever you can right now to get Hector and this message on the airwaves?
↗ View in Meta Ad Library (the live creative — image/video/layout)
| Overall score | 33.9/100 |
| Spend / Reach / Long. / Eff. | 25.8 · 51.9 · 4.1 · 53.7 |
| Spend range | USD 500–599 |
| Impressions | 8,000 – 8,999 |
| CPM (≈ $/1k impr) | USD 64.65 |
| Est. audience size | — |
| Days live | 16 (2026-03-13 → 2026-03-29) |
| Created | 2026-03-11 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | FL — Hector Mujica |
| Surfaced by | “senate:Hector Mujica” |
| Issue | democracy elections |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | money cash |
| Call to action | donate |
| Standout element | stark black video placeholder with play button creating a sense of an unreleased, urgent story waiting to be funded |
| Tactic | Classic fundraising urgency tactic pitting grassroots donors against opponent's corporate war chest, framing donations as the only way to get the truth on air before being drowned out. |
| Florida | 54.3% |
| California | 8.6% |
| New York | 3.1% |
| Texas | 3.1% |
| Pennsylvania | 2.0% |
| Illinois | 1.6% |
| Washington | 1.6% |
| 18-24 · female | 0.2% |
| 45-54 · male | 2.8% |
| 65+ · male | 16.8% |
| 65+ · female | 46.8% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 6.6% |
| 55-64 · female | 14.4% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 4.8% |
| 18-24 · male | 0.3% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 1.7% |
| 35-44 · female | 2.2% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 1.0% |
| 25-34 · female | 1.0% |
| 18-24 · unknown | 0.1% |
| 65+ · unknown | 0.8% |