Tom Willis WV US Inactive
Tom Willis Victory
Ad copy
Yes, unfortunately, this photo is real... That's Sen. Shelley Moore Capito with Nancy Pelosi. I can assure you West Virginia, I will never play for the radical Democrats. Senator Capito has voted with democrat lawmakers too many times. She voted to support 'Red Flag' Gun Confiscation, she voted with Pelosi against repealing Obamacare, she voted to repeal the Defense of Marriage Act, and she voted to fund Planned Parenthood. Enough is enough. Vote Tom Willis for U.S. Senate in the upcoming Republican Primary. It's time for a change.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 40.1/100 |
| Spend / Reach / Long. / Eff. | 25.8 · 66.9 · 3.0 · 64.8 |
| Spend range | USD 500–599 |
| Impressions | 35,000 – 39,999 |
| CPM (≈ $/1k impr) | USD 14.65 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 12 (2026-05-01 → 2026-05-13) |
| Created | 2026-05-01 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | WV — Tom Willis |
| Surfaced by | “senate:Tom Willis” |
🧠 AI analysis
| Issue | guns |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | opponent |
| Symbols | guns 2a |
| Call to action | vote |
| Standout element | baseball bat labeled 'DEMOCRATS' overlaid on a real photo of the opponent with Nancy Pelosi, making the association visceral and literal |
| Tactic | The ad uses a real, damaging photo of the opponent with the unpopular Nancy Pelosi combined with a sports metaphor ('batting for the wrong team') to make a RINO attack feel both factual and culturally resonant to West Virginia conservatives. |
Where it ran (delivery by region)
| West Virginia | 92.8% |
| Ohio | 1.0% |
| Pennsylvania | 1.0% |
| Virginia | 0.8% |
| Florida | 0.7% |
| Maryland | 0.6% |
| Texas | 0.3% |
Who saw it (delivery)
| 18-24 · female | 0.5% |
| 45-54 · male | 9.1% |
| 65+ · male | 26.5% |
| 65+ · female | 22.4% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 16.1% |
| 55-64 · female | 10.2% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 4.5% |
| 18-24 · male | 1.4% |
| 35-44 · unknown | 0.0% |
| 35-44 · male | 3.8% |
| 35-44 · female | 1.7% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 2.5% |
| 25-34 · female | 0.7% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.2% |
