Mary Peltola US Inactive
Mary Peltola for Congress
Restricting Bottom Trawling | Mary Peltola for Congress
Mary has proposed legislation that would restrict bottom trawling in order to save Alaska fisheries.
Ad copy
Mary has proposed legislation that would restrict bottom trawling in order to save Alaska fisheries. Chip in today, and we can keep fighting to preserve and rehabilitate our fisheries for generations to come. With your support, we can continue protecting Alaska fisheries with proven, adaptive management strategies that make us all better off.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 49.7/100 |
| Spend / Reach / Long. / Eff. | 27.6 · 81.7 · 14.9 · 74.5 |
| Spend range | USD 600–699 |
| Impressions | 150,000 – 174,999 |
| CPM (≈ $/1k impr) | USD 4.0 |
| Est. audience size | 5,001 – 10,000 |
| Days live | 55 (2024-06-08 → 2024-08-02) |
| Created | 2024-06-08 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | AK — Mary Peltola |
| Surfaced by | “senate:Mary Peltola” |
🧠 AI analysis
| Issue | energy environment |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | pride |
| Production tier | professional |
| Who pictured | candidate |
| Symbols | farm rural |
| Call to action | donate |
| Standout element | Candidate standing on an Alaskan shoreline with dramatic snow-capped mountains behind her, visually anchoring her identity to the landscape she seeks to protect |
| Tactic | The ad pairs a personal policy quote with stunning Alaskan scenery to make Peltola's environmental stewardship feel authentic and place-rooted, then pivots to a donation ask framed as protecting future generations. |
Where it ran (delivery by region)
| Alaska | 99.9% |
| Unknown | 0.1% |
Who saw it (delivery)
| 65+ · unknown | 0.2% |
| 25-34 · female | 12.6% |
| 55-64 · unknown | 0.1% |
| 18-24 · unknown | 0.2% |
| 25-34 · unknown | 0.3% |
| 35-44 · unknown | 0.3% |
| 35-44 · female | 12.0% |
| 45-54 · male | 8.2% |
| 25-34 · male | 11.3% |
| 45-54 · female | 8.5% |
| 18-24 · male | 5.4% |
| 55-64 · male | 6.5% |
| 35-44 · male | 10.5% |
| 65+ · female | 6.1% |
| 65+ · male | 5.2% |
| 18-24 · female | 5.3% |
| 55-64 · female | 7.2% |
| 45-54 · unknown | 0.1% |
