Hector Mujica US Inactive
Hector Mujica for Florida
Flip Florida Blue >>
Together, we can flip Florida BLUE.
Ad copy
The results of the Miami mayoral race prove that Democrats can win in Florida. After years of being written off, after national headlines claimed Florida was lost for Democrats, voters in Miami showed something powerful – that the momentum to flip Florida blue is real. Now, we have a chance to bring this change statewide. First the mayoral office. Next the Senate. Can you help us fight back and take advantage of this Miami win and turn all of Florida blue by rushing a $5 donation right now?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 18.9/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 24.3 · 0.0 · 51.2 |
| Spend range | <USD 99 |
| Impressions | 100 – 999 |
| CPM (≈ $/1k impr) | USD 90.08 |
| Est. audience size | — |
| Days live | 1 (2025-12-15 → 2025-12-16) |
| Created | 2025-12-12 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | FL — Hector Mujica |
| Surfaced by | “senate:Hector Mujica” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | hope |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Candidate posed in front of a bold blue silhouette of Florida on a dark navy background with a yellow 'DONATE' bar anchoring the bottom |
| Tactic | The ad leverages momentum framing — citing the Miami mayoral win as proof of concept — to convert enthusiasm into small-dollar donations with an urgency-driven ask. |
Where it ran (delivery by region)
| Florida | 76.0% |
| New York | 3.5% |
| California | 2.8% |
| Ohio | 1.6% |
| Massachusetts | 1.6% |
| Illinois | 1.6% |
| Texas | 1.2% |
Who saw it (delivery)
| 18-24 · female | 0.8% |
| 18-24 · male | 3.9% |
| 25-34 · female | 1.6% |
| 25-34 · male | 7.5% |
| 35-44 · female | 1.2% |
| 35-44 · male | 2.0% |
| 45-54 · female | 2.0% |
| 45-54 · male | 4.7% |
| 55-64 · female | 5.1% |
| 55-64 · male | 9.4% |
| 55-64 · unknown | 0.4% |
| 65+ · female | 29.5% |
| 65+ · male | 31.9% |
