Janet Mills US Inactive
Mills for Maine
Chip in: Defeat Susan Collins 🔴
Donate today >>
Ad copy
I wanted you to be among the first to hear: I’m Maine Governor Janet Mills, and I’m officially running for Senate to defeat Susan Collins. Susan Collins has too often put party politics and special interests ahead of Maine families – and she’s backed by massive GOP cash. But I’m no stranger to a tough fight. I’m running to make sure Maine has a fighter in the Senate who will champion our state’s priorities and stand up for our democracy. Please, chip in $5 or anything you can today to help me unseat Susan Collins >>
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 42.7/100 |
| Spend / Reach / Long. / Eff. | 44.9 · 70.7 · 0.8 · 54.4 |
| Spend range | USD 3,000–3,499 |
| Impressions | 50,000 – 59,999 |
| CPM (≈ $/1k impr) | USD 59.08 |
| Est. audience size | — |
| Days live | 4 (2025-10-14 → 2025-10-18) |
| Created | 2025-10-14 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Janet Mills |
| Surfaced by | “senate:Janet Mills” |
🧠 AI analysis
| 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 | Casual self-recorded video style with bold subtitle 'need you on my team' creating intimate direct-to-donor appeal |
| Tactic | The ad uses a personal announcement framing — 'be among the first to hear' — combined with a contrast attack on Collins' GOP ties to trigger urgency and donor loyalty simultaneously. |
Where it ran (delivery by region)
| Maine | 16.6% |
| California | 9.3% |
| Massachusetts | 7.9% |
| New York | 6.6% |
| Florida | 4.1% |
| Pennsylvania | 3.7% |
| New Jersey | 3.1% |
Who saw it (delivery)
| 18-24 · female | 0.4% |
| 45-54 · male | 3.9% |
| 65+ · male | 21.4% |
| 65+ · female | 36.2% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 8.7% |
| 55-64 · female | 11.4% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 4.7% |
| 18-24 · male | 0.7% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 3.4% |
| 35-44 · female | 3.7% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 2.1% |
| 25-34 · female | 2.0% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.8% |
