Dr. Roger Marshall US Inactive
KANSANS FOR MARSHALL
Stop the radical left >>>
Stop the radical left >>>
Chip in now.
Chip in now.
Ad copy
BREAKING: My liberal opponent Barbara Bollier — Chuck Schumer’s HAND-PICKED candidate — has set fundraising records. Chip in $5 NOW to help us fight back and defend OUR Republican majority >>>
BREAKING: My liberal opponent Barbara Bollier — Chuck Schumer’s HAND-PICKED candidate — has set fundraising records. Chip in $5 NOW to help us fight back and defend OUR Republican majority >>>
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 46.1/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 72.4 · 13.5 · 60.3 |
| Spend range | USD 1,500–1,999 |
| Impressions | 60,000 – 69,999 |
| CPM (≈ $/1k impr) | USD 26.92 |
| Est. audience size | — |
| Days live | 50 (2020-09-15 → 2020-11-04) |
| Created | 2020-09-14 |
| Creative variants | 2 body · 2 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | KS — Roger Marshall |
| Surfaced by | “senate:KS — Roger Marshall” |
🧠 AI analysis
| Issue | economy taxes |
| Framing | attack opponent |
| Message type | fundraising |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | opponent |
| Symbols | none |
| Call to action | donate |
| Standout element | Desaturated black-and-white photo of opponent looming over a Fox 4 news clipping on a dark blue background |
| Tactic | Urgency-driven fundraising appeal that weaponizes the opponent's own fundraising success as a threat, using borrowed Fox News credibility and a low $5 ask to convert fear of 'Schumer's hand-picked candidate' into immediate donor action. |
Where it ran (delivery by region)
| Kansas | 9.7% |
| Texas | 9.4% |
| California | 8.8% |
| Florida | 5.9% |
| New York | 3.7% |
| Illinois | 3.3% |
| Missouri | 3.1% |
Who saw it (delivery)
| 55-64 · unknown | 0.3% |
| 55-64 · male | 19.8% |
| 25-34 · female | 0.7% |
| 45-54 · unknown | 0.1% |
| 35-44 · male | 5.1% |
| 45-54 · female | 3.0% |
| 25-34 · male | 4.1% |
| 65+ · female | 17.1% |
| 18-24 · male | 2.0% |
| 18-24 · unknown | 0.0% |
| 55-64 · female | 8.8% |
| 65+ · male | 27.5% |
| 18-24 · female | 0.3% |
| 45-54 · male | 9.4% |
| 65+ · unknown | 0.4% |
| 35-44 · female | 1.2% |
| 35-44 · unknown | 0.1% |
| 25-34 · unknown | 0.1% |
