COMMITTEE TO ELECT ALAN GRAYSON
Florida is not a “red state”—we just aren’t registering Democratic voters. Thanks to the disappearance of Team Blue’s voter registration efforts during COVID, there are now fewer Florida Democrats than there were in 2008, even though 3,250,000 more people live here now. But in just one year, 2008, Florida registered 662,268 Democrats to vote, thanks to President Obama. Here's what I think: Florida can register 1,000,000 more Democrats this year, and become blue again. WITH YOUR HELP. We have to hire canvassers to go door to door to register voters. And we have to pay those canvassers. Will you join in that effort? As President Obama would say, are you in?
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| Overall score | 40.8/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 63.8 · 7.4 · 53.8 |
| Spend range | USD 1,500–1,999 |
| Impressions | 25,000 – 29,999 |
| CPM (≈ $/1k impr) | USD 63.62 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 28 (2024-02-15 → 2024-03-14) |
| Created | 2024-02-15 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | FL — Alan Grayson |
| Surfaced by | “senate:Alan Grayson” |
| Issue | democracy elections |
| Framing | attack opponent |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | opponent |
| Symbols | none |
| Call to action | donate |
| Standout element | Disheveled Trump hair photo paired with bold blue DEFEAT headline creates visceral contrast |
| Tactic | The ad uses an unflattering Trump image combined with a rhetorical question and voter registration urgency to convert anti-Trump emotion into ActBlue donations. |
| California | 14.4% |
| Florida | 9.5% |
| New York | 8.0% |
| Texas | 6.4% |
| Washington | 4.3% |
| Pennsylvania | 4.3% |
| Massachusetts | 3.7% |
| 25-34 · unknown | 0.0% |
| 65+ · female | 36.5% |
| 45-54 · unknown | 0.1% |
| 18-24 · female | 0.1% |
| 55-64 · unknown | 0.3% |
| 35-44 · female | 1.3% |
| 45-54 · male | 4.3% |
| 55-64 · male | 9.5% |
| 45-54 · female | 4.4% |
| 35-44 · unknown | 0.0% |
| 35-44 · male | 1.9% |
| 55-64 · female | 13.2% |
| 65+ · male | 26.0% |
| 65+ · unknown | 0.8% |
| 25-34 · female | 0.7% |
| 25-34 · male | 0.8% |
| 18-24 · male | 0.1% |