Mary Peltola US Inactive
Mary Peltola for Congress
Ad copy
There's no one more dedicated to our veterans and active servicemembers than Mary. As a military mom, she's looking out for our troops and securing real wins for the people who are putting their lives on the line for us. Click here, and see how Mary is looking out for our servicemembers and veterans by standing up to Nick Begich. Together, we can beat Nick and keep securing wins for our servicemembers.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 55.5/100 |
| Spend / Reach / Long. / Eff. | 44.9 · 95.7 · 8.8 · 72.8 |
| Spend range | USD 3,000–3,499 |
| Impressions | 600,000 – 699,999 |
| CPM (≈ $/1k impr) | USD 5.0 |
| Est. audience size | 50,001 – 100,000 |
| Days live | 33 (2024-10-04 → 2024-11-06) |
| Created | 2024-10-04 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | AK — Mary Peltola |
| Surfaced by | “senate:Mary Peltola” |
🧠 AI analysis
| Issue | veterans |
| Framing | contrast comparison |
| Message type | persuasion |
| Emotional appeal | pride |
| Production tier | semi pro |
| Who pictured | opponent, veterans military |
| Symbols | military |
| Call to action | learn more |
| Standout element | Desaturated faded image of opponent Nick Begich overlaid with 'ACTIVE DUTY' text, visually implicating him as a threat to servicemembers |
| Tactic | The ad uses a 'military mom' identity credential to build emotional trust while framing the opponent as someone who needs to be stood up to, turning veterans' welfare into a contrast attack. |
Where it ran (delivery by region)
| Alaska | 100.0% |
| Unknown | 0.0% |
Who saw it (delivery)
| 18-24 · female | 12.3% |
| 45-54 · male | 5.9% |
| 65+ · male | 2.8% |
| 65+ · female | 2.8% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 4.1% |
| 55-64 · female | 3.2% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 4.0% |
| 18-24 · male | 14.0% |
| 35-44 · unknown | 0.3% |
| 35-44 · male | 10.7% |
| 35-44 · female | 8.1% |
| 25-34 · unknown | 0.3% |
| 25-34 · male | 17.7% |
| 25-34 · female | 12.8% |
| 18-24 · unknown | 0.8% |
| 65+ · unknown | 0.1% |
