Cory Booker US Inactive
CORY BOOKER FOR SENATE
We have to fight back
Ad copy
I’m sounding the alarm and I hope you will answer this call because the power of the people is greater than the people in power. Together, we have to fight back. We have to push back. We have to do everything we can. But it’s going to take more of us stepping up. It’s going to take more pressure. If you’re with me in this fight, please make a contribution to my campaign right now. Your donation will help me to continue to criss-cross the country going to red states and blue states, ringing the alarm about this horrible bill that will be a disaster for millions of Americans from coast-to-coast.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 44.7/100 |
| Spend / Reach / Long. / Eff. | 49.0 · 73.9 · 1.9 · 53.9 |
| Spend range | USD 4,500–4,999 |
| Impressions | 70,000 – 79,999 |
| CPM (≈ $/1k impr) | USD 63.33 |
| Est. audience size | — |
| Days live | 8 (2025-06-24 → 2025-07-02) |
| Created | 2025-06-24 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | NJ — Cory Booker |
| Surfaced by | “senate:Cory Booker” |
🧠 AI analysis
| Issue | healthcare |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | diy amateur |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | extreme close-up selfie-style video of Booker's furrowed, intense face conveying raw alarm |
| Tactic | Urgent, direct-to-camera authenticity tactic lowers the production polish intentionally to create intimacy and personal urgency, driving small-dollar donations by framing the fight as a people-powered movement against harmful legislation. |
Where it ran (delivery by region)
| California | 19.6% |
| New Jersey | 8.9% |
| New York | 7.7% |
| Florida | 5.7% |
| Texas | 4.4% |
| Pennsylvania | 3.9% |
| Washington | 3.2% |
Who saw it (delivery)
| 18-24 · female | 0.7% |
| 45-54 · male | 2.8% |
| 65+ · male | 8.6% |
| 65+ · female | 40.2% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 4.8% |
| 55-64 · female | 20.8% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 9.1% |
| 18-24 · male | 0.7% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 1.8% |
| 35-44 · female | 5.1% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 1.5% |
| 25-34 · female | 2.9% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.5% |
