Graham Platner US Inactive
GRAHAM FOR MAINE
Oyster farmer Graham Platner seeks to bring a new perspective to US Senate
Graham Platner, a Maine oyster farmer and military veteran, is looking to shake up how politics are played in Washington. The Democratic candidate has his sights set on the U.S. Senate seat held by Republican Sen. Susan Collins.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 51.2/100 |
| Spend / Reach / Long. / Eff. | 47.8 · 90.1 · 0.3 · 66.7 |
| Spend range | USD 4,000–4,499 |
| Impressions | 350,000 – 399,999 |
| CPM (≈ $/1k impr) | USD 11.33 |
| Est. audience size | — |
| Days live | 2 (2026-06-09 → 2026-06-11) |
| Created | 2026-06-08 |
| Creative variants | 0 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Graham Platner |
| Surfaced by | “senate:Graham Platner” |
🧠 AI analysis
| Issue | candidate character bio |
| Framing | positive candidate |
| Message type | awareness |
| Emotional appeal | empathy |
| Production tier | semi pro |
| Who pictured | candidate, veterans military |
| Symbols | farm rural |
| Call to action | learn more |
| Standout element | Candidate in work clothes outdoors with oyster farming equipment, conveying authentic blue-collar identity |
| Tactic | Borrowed credibility tactic: leverages a local news outlet (WMTW) story to frame the candidate as an outsider change-agent, lending third-party authenticity to his everyman farmer-veteran narrative. |
Where it ran (delivery by region)
| California | 11.9% |
| Texas | 9.0% |
| Florida | 6.5% |
| New York | 5.2% |
| Pennsylvania | 4.0% |
| North Carolina | 3.7% |
| Ohio | 3.7% |
Who saw it (delivery)
| 18-24 · female | 5.6% |
| 45-54 · unknown | 0.1% |
| Unknown · female | 0.0% |
| 65+ · unknown | 0.1% |
| 65+ · male | 16.4% |
| 65+ · female | 8.0% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 8.3% |
| 55-64 · female | 2.5% |
| 45-54 · male | 6.5% |
| 18-24 · male | 16.3% |
| 45-54 · female | 1.7% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 9.6% |
| 35-44 · female | 2.3% |
| 25-34 · unknown | 0.2% |
| 25-34 · male | 17.7% |
| 25-34 · female | 4.1% |
| 18-24 · unknown | 0.3% |
| Unknown · male | 0.0% |
