Tom Cotton US Inactive
COTTON FOR SENATE, INC.
Stop the madness
Sign now.
Ad copy
First, Democrats tried to end voter ID and fund their campaigns with our tax dollars. Now, they’re trying to let illegal immigrants vote in our elections. Stand with me to stop them and protect our elections. If you’re with me, SIGN my petition below.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 47.2/100 |
| Spend / Reach / Long. / Eff. | 34.7 · 81.7 · 2.8 · 69.6 |
| Spend range | USD 1,000–1,499 |
| Impressions | 150,000 – 174,999 |
| CPM (≈ $/1k impr) | USD 7.69 |
| Est. audience size | — |
| Days live | 11 (2022-10-21 → 2022-11-01) |
| Created | 2022-10-20 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | AR — Tom Cotton |
| Surfaced by | “senate:Tom Cotton” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | list building survey |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | us flag |
| Call to action | sign petition |
| Standout element | torn paper reveal effect splitting a Washington Free Beacon headline from a dark dramatic candidate portrait with a bold red CTA button |
| Tactic | The ad uses a fear-and-urgency tactic by citing a media headline as borrowed credibility to legitimize the threat, then channels that anxiety directly into a low-friction petition sign-up to build the donor/supporter list. |
Where it ran (delivery by region)
| Texas | 7.2% |
| Florida | 6.4% |
| California | 4.6% |
| Ohio | 4.5% |
| Pennsylvania | 4.2% |
| Michigan | 4.0% |
| New York | 3.9% |
Who saw it (delivery)
| 13-17 · female | 0.0% |
| 45-54 · female | 2.3% |
| 35-44 · unknown | 0.0% |
| 45-54 · unknown | 0.1% |
| 18-24 · male | 0.5% |
| 25-34 · female | 0.6% |
| 65+ · unknown | 0.4% |
| 55-64 · female | 10.7% |
| 35-44 · male | 1.5% |
| 25-34 · male | 1.5% |
| 13-17 · male | 0.0% |
| 45-54 · male | 4.6% |
| 65+ · female | 32.3% |
| 65+ · male | 29.9% |
| 55-64 · male | 14.7% |
| 25-34 · unknown | 0.0% |
| 35-44 · female | 0.7% |
| 18-24 · female | 0.2% |
| 55-64 · unknown | 0.2% |
| 18-24 · unknown | 0.0% |
