Janet Mills US Inactive
Mills for Maine
It’s official: I’m running 🔵
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Ad copy
Maine Governor Janet Mills here. It’s official: I'm running for the U.S. Senate because Maine needs a fighter who knows how to stand up to bullies. Susan Collins has failed time and again. But Republicans are ready to spend millions attacking us to defend her seat, so I need your help. This is going to be the most consequential Senate race in the country. Can I count on you to rush a donation to my campaign today?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 39.0/100 |
| Spend / Reach / Long. / Eff. | 47.8 · 61.7 · 0.6 · 45.7 |
| Spend range | USD 4,000–4,499 |
| Impressions | 20,000 – 24,999 |
| CPM (≈ $/1k impr) | USD 188.87 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 3 (2025-10-14 → 2025-10-17) |
| Created | 2025-10-13 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Janet Mills |
| Surfaced by | “senate:Janet Mills” |
🧠 AI analysis
| Issue | other |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | unknown |
| Who pictured | none |
| Symbols | none |
| Call to action | donate |
| Standout element | Blank white image with no visual content — ad relies entirely on copy |
| Tactic | The ad uses urgency and underdog framing ('rush a donation,' 'millions attacking us') to drive immediate fundraising response by positioning Mills as a fighter against both a vulnerable incumbent and outside money. |
Where it ran (delivery by region)
| California | 16.4% |
| Florida | 8.0% |
| New York | 7.2% |
| Massachusetts | 5.3% |
| Texas | 5.0% |
| Pennsylvania | 4.2% |
| Ohio | 3.4% |
Who saw it (delivery)
| 18-24 · female | 0.1% |
| 45-54 · male | 1.4% |
| 65+ · male | 26.3% |
| 65+ · female | 50.8% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 5.7% |
| 55-64 · female | 9.8% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 2.1% |
| 18-24 · male | 0.1% |
| 35-44 · unknown | 0.0% |
| 35-44 · male | 0.7% |
| 35-44 · female | 0.9% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 0.2% |
| 25-34 · female | 0.6% |
| 65+ · unknown | 1.0% |
