Alan Grayson US Inactive
COMMITTEE TO ELECT ALAN GRAYSON
Help turn Florida blue >>
Ad copy
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?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 43.8/100 |
| Spend / Reach / Long. / Eff. | 43.1 · 70.7 · 5.8 · 55.6 |
| Spend range | USD 2,500–2,999 |
| Impressions | 50,000 – 59,999 |
| CPM (≈ $/1k impr) | USD 49.99 |
| Est. audience size | — |
| Days live | 22 (2024-02-19 → 2024-03-12) |
| Created | 2024-02-19 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | FL — Alan Grayson |
| Surfaced by | “senate:Alan Grayson” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Grayson's intense, furrowed-brow expression paired with a loud tropical shirt creating an unconventional, attention-grabbing candidate frame |
| Tactic | The ad leverages Obama nostalgia and a concrete numerical goal (1,000,000 new Democrats) to create urgency and tie a donation ask directly to a tangible voter registration mission. |
Where it ran (delivery by region)
| Florida | 22.9% |
| California | 11.9% |
| New York | 7.1% |
| Texas | 4.2% |
| Massachusetts | 3.4% |
| New Jersey | 3.2% |
| Pennsylvania | 3.2% |
Who saw it (delivery)
| 18-24 · unknown | 0.0% |
| 25-34 · female | 0.6% |
| 25-34 · unknown | 0.0% |
| 65+ · unknown | 0.8% |
| 18-24 · male | 0.3% |
| 35-44 · unknown | 0.1% |
| 35-44 · female | 0.7% |
| 45-54 · male | 3.2% |
| 35-44 · male | 1.3% |
| 55-64 · unknown | 0.3% |
| 25-34 · male | 0.8% |
| 45-54 · female | 2.2% |
| 55-64 · female | 10.0% |
| 55-64 · male | 10.0% |
| 65+ · female | 40.6% |
| 65+ · male | 28.8% |
| 18-24 · female | 0.2% |
| 45-54 · unknown | 0.1% |
