Tom Willis WV US Inactive
Tom Willis WV
Ad copy
Senate President Craig Blair voted to allow "woke" liberal physicians to perform dangerous sex-change experiments on children. These life-altering drugs block children from entering puberty, often sterilizing them for life. They can even result in death. Senator Craig Blair should be ashamed of himself for thinking that children can "consent". When Craig Blair is in the WV Senate, our children are at risk. On May 14th, vote Tom Willis for WV Senate in the upcoming Republican Primary. It's time to protect West Virginia's kids. Roll Call: https://www.wvlegislature.gov/legisdocs/2023/RS/votes/senate/03-10-0568.pdf
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 27.1/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 43.0 · 0.3 · 65.1 |
| Spend range | <USD 99 |
| Impressions | 3,000 – 3,999 |
| CPM (≈ $/1k impr) | USD 14.14 |
| Est. audience size | 10,001 – 50,000 |
| Days live | 2 (2024-03-16 → 2024-03-18) |
| Created | 2024-03-16 |
| Creative variants | 1 body · 0 headline |
| Platforms | |
| Languages | en |
| Candidate | WV — Tom Willis |
| Surfaced by | “senate:Tom Willis” |
🧠 AI analysis
| Issue | healthcare |
| Framing | contrast comparison |
| Message type | persuasion |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | candidate, opponent, medical |
| Symbols | military, family |
| Call to action | vote |
| Standout element | Side-by-side contrast pairing opponent with drag makeup imagery against candidate in military uniform |
| Tactic | The ad uses fear-based contrast framing — juxtaposing an unflattering cultural image next to a military uniform — to trigger parental protective instincts and drive Republican primary votes against an incumbent. |
Where it ran (delivery by region)
| West Virginia | 89.8% |
| Maryland | 9.1% |
| Virginia | 1.0% |
| Unknown | 0.1% |
Who saw it (delivery)
| 18-24 · male | 1.0% |
| 65+ · male | 17.7% |
| 18-24 · female | 0.5% |
| 45-54 · unknown | 0.2% |
| 65+ · unknown | 0.2% |
| 65+ · female | 23.0% |
| 55-64 · male | 14.0% |
| 25-34 · male | 4.4% |
| 35-44 · male | 7.2% |
| 35-44 · unknown | 0.1% |
| 35-44 · female | 3.2% |
| 55-64 · female | 10.9% |
| 45-54 · male | 9.8% |
| 45-54 · female | 5.8% |
| 25-34 · female | 1.9% |
| 55-64 · unknown | 0.1% |
| 18-24 · unknown | 0.1% |
