Jeanne Shaheen US Inactive
SHAHEEN FOR SENATE
Colorado Corky ran a scam foundation before moving to NH
Ad copy
Colorado Corky Messner moved to New Hampshire last year to try and buy a Senate seat. Even worse, back in Colorado, he’s facing a potential criminal probe for his sham foundation that took hundreds of thousands of dollars in donations for college scholarships -- but only helped one student in 10 years! Colorado Corky is out for himself, not New Hampshire.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 44.1/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 73.9 · 2.8 · 61.3 |
| Spend range | USD 1,500–1,999 |
| Impressions | 70,000 – 79,999 |
| CPM (≈ $/1k impr) | USD 23.33 |
| Est. audience size | 10,001 – 50,000 |
| Days live | 11 (2020-10-23 → 2020-11-03) |
| Created | 2020-10-23 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | NH — Jeanne Shaheen |
| Surfaced by | “senate:Jeanne Shaheen” |
🧠 AI analysis
| Issue | candidate character bio |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | none |
| Call to action | learn more |
| Standout element | Washington Post citation overlaid on rural Colorado landscape reinforcing the 'outsider' narrative |
| Tactic | The ad weaponizes a credible newspaper citation alongside a repeated 'Colorado Corky' nickname to brand the opponent as a self-serving carpetbagger with a fraudulent charity, leveraging both geographic otherness and character attack simultaneously. |
Where it ran (delivery by region)
| New Hampshire | 100.0% |
Who saw it (delivery)
| 25-34 · male | 1.1% |
| 35-44 · male | 1.2% |
| 45-54 · unknown | 0.1% |
| 18-24 · unknown | 0.1% |
| 35-44 · unknown | 0.2% |
| 25-34 · unknown | 0.2% |
| 55-64 · unknown | 0.1% |
| 65+ · male | 0.3% |
| 18-24 · male | 0.5% |
| 45-54 · male | 1.5% |
| 55-64 · male | 1.1% |
| 65+ · female | 1.3% |
| 45-54 · female | 21.9% |
| 55-64 · female | 11.9% |
| 18-24 · female | 10.7% |
| 35-44 · female | 24.3% |
| 25-34 · female | 23.3% |
| 65+ · unknown | 0.0% |
