Janet Mills US Inactive
Mills for Maine
Millions are going to be spent against us
Make a contribution today so Gov. Mills can fight back.
Ad copy
The Maine GOP is planning on spending millions against us. Recently, they announced their plans to book a whopping $3.9 million in TV attack ads against Governor Mills. This won’t be the last attack we face this election year. My opponent will be well-funded by national special interests who will stop at nothing to erase all the progress we’ve made in Maine. Help us fight back by rushing a $10 donation right now so we can stay ahead →
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 51.8/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 69.3 · 41.6 · 57.9 |
| Spend range | USD 1,500–1,999 |
| Impressions | 45,000 – 49,999 |
| CPM (≈ $/1k impr) | USD 36.83 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 152 (2022-03-20 → 2022-08-19) |
| Created | 2022-03-19 |
| 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 | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | unknown |
| Who pictured | none |
| Symbols | none |
| Call to action | donate |
| Standout element | Facebook content-removed notice replacing the actual ad creative, making the ad itself invisible |
| Tactic | The ad leverages a threat-and-urgency fundraising frame — citing a specific $3.9M opponent ad buy — to drive small-dollar donations, though the creative was removed for disclaimer non-compliance. |
Where it ran (delivery by region)
| Maine | 54.8% |
| Massachusetts | 6.6% |
| New York | 4.4% |
| New Hampshire | 3.7% |
| California | 3.3% |
| Vermont | 2.7% |
| Florida | 2.1% |
Who saw it (delivery)
| 18-24 · unknown | 0.0% |
| 55-64 · female | 13.0% |
| 35-44 · male | 2.0% |
| 25-34 · male | 0.9% |
| 65+ · male | 22.0% |
| 65+ · female | 39.0% |
| 55-64 · male | 8.0% |
| 65+ · unknown | 0.8% |
| 35-44 · female | 3.2% |
| 35-44 · unknown | 0.1% |
| 45-54 · male | 3.3% |
| 25-34 · female | 1.0% |
| 45-54 · unknown | 0.1% |
| 18-24 · female | 0.1% |
| 18-24 · male | 0.1% |
| 55-64 · unknown | 0.3% |
| 25-34 · unknown | 0.1% |
| 45-54 · female | 6.0% |
