Jennifer Jenkins For Florida US Inactive
Jennifer Jenkins For Florida
humbly asking
Ad copy
Democrats, hereโs the deal: โ We just flipped the Miami Mayorโs Office BLUE for the first time in 30 years โ Young voters are turning out in droves โ Extremist candidates are losing ground We can defeat my MAGA opponent and flip Floridaโs Senate seat BLUE โ but itโll take all hands on deck to win this race. ๐๐๐ง ๐ ๐๐จ๐ฎ๐ง๐ญ ๐จ๐ง ๐ฒ๐จ๐ฎ ๐ญ๐จ ๐๐ก๐ข๐ฉ ๐ข๐ง $๐๐ ๐จ๐ซ ๐๐ง๐ฒ๐ญ๐ก๐ข๐ง๐ ๐ฒ๐จ๐ฎ ๐๐๐ง ๐ญ๐จ ๐ก๐๐ฅ๐ฉ ๐ฆ๐ ๐ค๐๐๐ฉ ๐ฎ๐ฉ ๐ญ๐ก๐ ๐ฆ๐จ๐ฆ๐๐ง๐ญ๐ฎ๐ฆ?
โ View in Meta Ad Library (the live creative โ image/video/layout)
Performance proxies
| Overall score | 25.6/100 |
| Spend / Reach / Long. / Eff. | 11.9 ยท 34.4 ยท 5.8 ยท 50.5 |
| Spend range | USD 100โ199 |
| Impressions | 1,000 โ 1,999 |
| CPM (โ $/1k impr) | USD 99.7 |
| Est. audience size | 5,001 โ 10,000 |
| Days live | 22 (2026-01-04 โ 2026-01-26) |
| Created | 2026-01-04 |
| Creative variants | 1 body ยท 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | FL โ Jennifer Jenkins |
| Surfaced by | โsenate:Jennifer Jenkinsโ |
๐ง 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 | Bold subtitle overlay 'We can flip this seat' in high-contrast blue-and-white text anchoring the candidate's direct-to-camera appeal |
| Tactic | Uses momentum framing โ citing recent Democratic wins โ to create urgency and lower the perceived risk of donating, then closes with a humble personal ask to soften the pitch. |
Where it ran (delivery by region)
| Florida | 83.5% |
| New York | 1.6% |
| California | 1.6% |
| Texas | 1.3% |
| Michigan | 1.3% |
| Pennsylvania | 0.9% |
| North Carolina | 0.8% |
Who saw it (delivery)
| 18-24 ยท male | 0.1% |
| 25-34 ยท female | 0.8% |
| 25-34 ยท male | 1.2% |
| 25-34 ยท unknown | 0.1% |
| 35-44 ยท female | 2.5% |
| 35-44 ยท male | 1.0% |
| 45-54 ยท female | 3.3% |
| 45-54 ยท male | 3.8% |
| 55-64 ยท female | 8.1% |
| 55-64 ยท male | 9.1% |
| 65+ ยท female | 32.7% |
| 65+ ยท male | 36.2% |
| 65+ ยท unknown | 1.0% |
