Jordan Wood US Inactive
JORDAN FOR MAINE
Will you chip in to help me defeat Susan Collins?
Can I count on your $10? >>
Ad copy
I’ll be blunt. This is going to be an incredibly close race. It won’t be easy to defeat Susan Collins and flip this critical Senate seat from red to blue – especially not when she’s raised a shocking $5.3 million to take me out. I’m up against my fundraising deadline, so it’s absolutely critical that I close the gap and show that my campaign has what it takes to defeat Susan Collins. Right now, I still need 1,000 more supporters to step up in these final hours to prove to everyone watching that we can win. Can I count on you to chip in $10?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 39.7/100 |
| Spend / Reach / Long. / Eff. | 25.8 · 61.7 · 10.2 · 61.0 |
| Spend range | USD 500–599 |
| Impressions | 20,000 – 24,999 |
| CPM (≈ $/1k impr) | USD 24.42 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 38 (2025-07-30 → 2025-09-06) |
| Created | 2025-07-30 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Jordan Wood |
| Surfaced by | “senate:Jordan Wood” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | diy amateur |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Selfie-style vertical video frame giving an intimate direct-to-camera confession of underdog urgency |
| Tactic | Classic grassroots fundraising urgency tactic using a fundraising deadline, opponent's war chest as a threat, and a specific donor count goal to trigger loss-aversion and small-dollar contributions. |
Where it ran (delivery by region)
| Maine | 100.0% |
Who saw it (delivery)
| 25-34 · female | 2.2% |
| 25-34 · male | 1.6% |
| 25-34 · unknown | 0.1% |
| 35-44 · female | 7.4% |
| 35-44 · male | 4.1% |
| 35-44 · unknown | 0.5% |
| 45-54 · female | 10.1% |
| 45-54 · male | 4.7% |
| 45-54 · unknown | 0.3% |
| 55-64 · female | 16.5% |
| 55-64 · male | 7.6% |
| 55-64 · unknown | 0.3% |
| 65+ · female | 29.7% |
| 65+ · male | 14.1% |
| 65+ · unknown | 0.8% |
