JORDAN FOR MAINE
If we win this race, we’ll win the ENTIRE Senate >>
If we win this race, we’ll win the ENTIRE Senate >>
Jordan needs you to chip in to help him defeat Susan Collins. Here’s why: – Trump LOST Maine by 7 points – If we win Maine, we win the ENTIRE Senate – But Collins has MILLIONS in the bank to sabotage Jordan’s chances We CAN win this, but our campaign started with $0 in the bank, and he can’t do it without you. Please, will you chip in any amount?
Jordan needs you to chip in to help him defeat Susan Collins. Here’s why: – Trump LOST Maine by 7 points – If we win Maine, we win the ENTIRE Senate – But Collins has MILLIONS in the bank to sabotage Jordan’s chances We CAN win this, but our campaign started with $0 in the bank, and he can’t do it without you. Please, will you chip in any amount?
↗ View in Meta Ad Library (the live creative — image/video/layout)
| Overall score | 34.9/100 |
| Spend / Reach / Long. / Eff. | 25.8 · 55.8 · 1.4 · 56.6 |
| Spend range | USD 500–599 |
| Impressions | 10,000 – 14,999 |
| CPM (≈ $/1k impr) | USD 43.96 |
| Est. audience size | — |
| Days live | 6 (2025-10-10 → 2025-10-16) |
| Created | 2025-10-10 |
| Creative variants | 2 body · 2 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Jordan Wood |
| Surfaced by | “senate:Jordan Wood” |
| 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 | Candidate filming a selfie video from inside a car wearing an L.L.Bean vest — deliberately low-fi and relatable |
| Tactic | Uses a classic grassroots fundraising urgency tactic — framing the underdog challenger against a cash-flush incumbent with a Senate-majority stakes argument to drive small-dollar donations. |
| California | 17.8% |
| Texas | 7.4% |
| Illinois | 6.9% |
| New York | 6.1% |
| Florida | 4.6% |
| New Jersey | 4.5% |
| Michigan | 4.1% |
| 25-34 · female | 1.2% |
| 25-34 · male | 1.0% |
| 25-34 · unknown | 0.0% |
| 35-44 · female | 2.2% |
| 35-44 · male | 2.2% |
| 35-44 · unknown | 0.1% |
| 45-54 · female | 4.4% |
| 45-54 · male | 3.6% |
| 45-54 · unknown | 0.2% |
| 55-64 · female | 13.2% |
| 55-64 · male | 9.7% |
| 55-64 · unknown | 0.3% |
| 65+ · female | 41.8% |
| 65+ · male | 19.5% |
| 65+ · unknown | 0.7% |