Janet Mills US Inactive
Mills for Maine
Chip in: Defeat Susan Collins 🔴
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Ad copy
For too long now, Susan Collins has failed to stand up to Donald Trump. That hurts Maine people. We can do better. We will do better. Join me in this fight – chip in $5 or anything you can today, and together we’ll stand up to flip this seat blue and build a brighter future.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 37.9/100 |
| Spend / Reach / Long. / Eff. | 49.0 · 59.2 · 0.3 · 43.0 |
| Spend range | USD 4,500–4,999 |
| Impressions | 15,000 – 19,999 |
| CPM (≈ $/1k impr) | USD 271.41 |
| Est. audience size | 10,001 – 50,000 |
| Days live | 2 (2025-10-14 → 2025-10-16) |
| 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 | candidate character bio |
| 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 kitchen setting with candidate speaking directly to camera, creating intimate authenticity |
| Tactic | Low-production selfie-style video paired with a direct opponent attack and a low-dollar fundraising ask creates urgency and accessibility, making the donate barrier feel small. |
Where it ran (delivery by region)
| New York | 13.1% |
| California | 12.2% |
| Massachusetts | 8.6% |
| Maine | 4.5% |
| Florida | 4.2% |
| Maryland | 4.0% |
| New Jersey | 3.8% |
Who saw it (delivery)
| 18-24 · female | 0.1% |
| 45-54 · male | 2.4% |
| 65+ · male | 21.7% |
| 65+ · female | 50.7% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 4.4% |
| 55-64 · female | 9.1% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 3.9% |
| 18-24 · male | 0.0% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 1.7% |
| 35-44 · female | 2.4% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 0.7% |
| 25-34 · female | 1.3% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 1.1% |
