Graham Platner US Inactive
GRAHAM FOR MAINE
Defeat Susan Collins >>
Defeat Susan Collins >>
I am counting on grassroots donors like you to chip in now if we're going to defeat Susan Collins and flip Maine blue.
I am counting on grassroots donors like you to chip in now if we're going to defeat Susan Collins and flip Maine blue.
Ad copy
Make a monthly donation now to help Graham Platner defeat Susan Collins, flip Maine blue, and take back the Senate for Democrats
Make a monthly donation now to help Graham Platner defeat Susan Collins, flip Maine blue, and take back the Senate for Democrats
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 52.5/100 |
| Spend / Reach / Long. / Eff. | 59.4 · 90.1 · 1.9 · 58.7 |
| Spend range | USD 10,000–14,999 |
| Impressions | 350,000 – 399,999 |
| CPM (≈ $/1k impr) | USD 33.33 |
| Est. audience size | — |
| Days live | 8 (2026-06-06 → 2026-06-14) |
| Created | 2026-06-06 |
| Creative variants | 2 body · 2 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Graham Platner |
| Surfaced by | “senate:Graham Platner” |
🧠 AI analysis
| Issue | jobs labor |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | workers labor |
| Symbols | none |
| Call to action | donate |
| Standout element | Union-logo shirt on speaker at mic with defiant 'We're not asking for handouts' subtitle reinforcing working-class authenticity |
| Tactic | Uses a relatable working-class surrogate delivering a dignity-over-charity message to shame inaction and convert that emotion into a monthly recurring donation against Susan Collins. |
Where it ran (delivery by region)
| Maine | 14.0% |
| California | 10.1% |
| Massachusetts | 7.7% |
| New York | 7.2% |
| Washington | 4.1% |
| Florida | 4.1% |
| Texas | 3.4% |
Who saw it (delivery)
| 18-24 · female | 0.2% |
| 45-54 · male | 8.5% |
| 65+ · male | 24.0% |
| 65+ · female | 21.1% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 12.4% |
| 55-64 · female | 8.0% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 3.9% |
| 18-24 · male | 1.0% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 9.3% |
| 35-44 · female | 3.2% |
| 25-34 · unknown | 0.2% |
| 25-34 · male | 5.4% |
| 25-34 · female | 1.5% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.7% |
