Mary Peltola US Inactive
Mary Peltola for Congress
Help Mary bring real infrastructure investments to Alaska
Tired of potholes? Mary has brought in over $8.7 billion in infrastructure investment statewide, including $212 million for the Interior, to improve our roads, bridges, docks, airports, and more so Alaskans can have the high-quality infrastructure they deserve.
Ad copy
Tired of potholes? Mary has brought in over $8.7 billion in infrastructure investment statewide, including $212 million for the Interior, to improve our roads, bridges, docks, airports, and more so Alaskans can have the high-quality infrastructure they deserve. Click here, and see what Mary is doing for the Interior. With your support, we can continue continue securing critical infrastructure funding for years to come.
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Performance proxies
| Overall score | 39.4/100 |
| Spend / Reach / Long. / Eff. | 11.9 · 65.4 · 6.9 · 73.5 |
| Spend range | USD 100–199 |
| Impressions | 30,000 – 34,999 |
| CPM (≈ $/1k impr) | USD 4.6 |
| Est. audience size | 10,001 – 50,000 |
| Days live | 26 (2024-09-11 → 2024-10-07) |
| Created | 2024-09-11 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | AK — Mary Peltola |
| Surfaced by | “senate:Mary Peltola” |
🧠 AI analysis
| Issue | housing |
| Framing | positive candidate |
| Message type | persuasion |
| Emotional appeal | empathy |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | farm rural |
| Call to action | learn more |
| Standout element | Large water-filled pothole dominating the foreground of a rural Alaskan road, viscerally illustrating the problem |
| Tactic | Problem-solution framing pairs a relatable local grievance (potholes) with a concrete dollar figure to make Peltola's legislative accomplishments tangible and personally relevant to Interior Alaska voters. |
Where it ran (delivery by region)
| Alaska | 100.0% |
Who saw it (delivery)
| 18-24 · female | 6.0% |
| 45-54 · male | 9.9% |
| 65+ · male | 4.3% |
| 65+ · female | 3.9% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 6.7% |
| 55-64 · female | 5.4% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 7.0% |
| 18-24 · male | 5.6% |
| 35-44 · unknown | 0.3% |
| 35-44 · male | 13.9% |
| 35-44 · female | 10.6% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 14.1% |
| 25-34 · female | 11.8% |
| 18-24 · unknown | 0.1% |
| 65+ · unknown | 0.1% |
