GRAHAM FOR MAINE
I’m not taking money from AIPAC or corporations, so any amount you can afford to give goes a long way.
My name is Graham Platner. I’m the Marine Corps veteran and oyster farmer running for Senate here in Maine against Susan Collins. My opponent has already been endorsed by AIPAC — an endorsement I will never get. Because what is happening right now in Gaza is a genocide. I need your help because we refuse to take money from AIPAC, and we refuse to take money from the billionaires who support it. So please, will you make a monthly donation now to my campaign to help me defeat Susan Collins, turn Maine blue, and take back the Senate for Democrats?
↗ View in Meta Ad Library (the live creative — image/video/layout)
| Overall score | 60.5/100 |
| Spend / Reach / Long. / Eff. | 72.5 · 100.0 · 12.4 · 56.9 |
| Spend range | USD 40,000–44,999 |
| Impressions | 1,000,000 – 0 |
| CPM (≈ $/1k impr) | USD 42.5 |
| Est. audience size | — |
| Days live | 46 (2025-08-27 → 2025-10-12) |
| Created | 2025-08-27 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Graham Platner |
| Surfaced by | “senate:Graham Platner” |
| Issue | foreign policy defense |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | anger |
| Production tier | diy amateur |
| Who pictured | candidate, veterans military |
| Symbols | none |
| Call to action | donate |
| Standout element | Candidate delivering direct-to-camera accusation of genocide in a casual outdoor setting with no production polish |
| Tactic | The ad uses moral outrage as a fundraising trigger — framing the AIPAC endorsement of the opponent as disqualifying and positioning the candidate's refusal of that money as a principled contrast that justifies donating. |
| California | 13.9% |
| New York | 10.3% |
| Maine | 9.5% |
| Massachusetts | 7.5% |
| Texas | 4.0% |
| Washington | 3.8% |
| Pennsylvania | 3.4% |
| 18-24 · female | 2.1% |
| 45-54 · male | 8.2% |
| 65+ · male | 7.9% |
| 65+ · female | 8.7% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 7.0% |
| 55-64 · female | 6.4% |
| 45-54 · unknown | 0.3% |
| 45-54 · female | 7.0% |
| 18-24 · male | 6.0% |
| 35-44 · unknown | 0.6% |
| 35-44 · male | 13.4% |
| 35-44 · female | 10.2% |
| 25-34 · unknown | 0.6% |
| 25-34 · male | 13.1% |
| 25-34 · female | 7.6% |
| 18-24 · unknown | 0.3% |
| 65+ · unknown | 0.3% |