Tom Willis WV US Inactive
Tom Willis Victory
Ad copy
When you move tens of thousands of people into communities without proper screening, you invite preventable risks. Capito spent $13 billion of our taxpayer money to relocate radical islamists into our country. Capito supported and funded Biden's program. Read More: https://www.breitbart.com/politics/2021/12/03/the-list-19-senate-republicans-give-biden-over-13b-to-resettle-unlimited-flow-of-afghans-across-their-states/ Roll Call: https://www.senate.gov/legislative/LIS/roll_call_votes/vote1171/vote_117_1_00477.htm?congress=117&session=1&vote=00477#position
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 28.7/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 45.5 · 2.2 · 67.0 |
| Spend range | <USD 99 |
| Impressions | 4,000 – 4,999 |
| CPM (≈ $/1k impr) | USD 11.0 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 9 (2026-01-14 → 2026-01-23) |
| Created | 2026-01-14 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | WV — Tom Willis |
| Surfaced by | “senate:Tom Willis” |
🧠 AI analysis
| Issue | immigration |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | opponent, candidate |
| Symbols | money cash, border |
| Call to action | learn more |
| Standout element | Photo of opponent Capito warmly shaking hands with Biden juxtaposed against inflammatory immigration attack text |
| Tactic | The ad uses a guilt-by-association tactic, pairing an image of Capito with Biden alongside inflammatory 'radical islamists' language to trigger fear and betrayal emotions among conservative primary voters. |
Where it ran (delivery by region)
| West Virginia | 94.2% |
| Pennsylvania | 0.9% |
| Ohio | 0.9% |
| Virginia | 0.7% |
| Kentucky | 0.6% |
| Maryland | 0.5% |
| Florida | 0.3% |
Who saw it (delivery)
| 18-24 · female | 0.3% |
| 45-54 · male | 8.0% |
| 65+ · male | 20.5% |
| 65+ · female | 23.1% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 17.4% |
| 55-64 · female | 14.4% |
| 45-54 · unknown | 0.0% |
| 45-54 · female | 5.3% |
| 18-24 · male | 0.8% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 4.2% |
| 35-44 · female | 1.6% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 3.0% |
| 25-34 · female | 0.8% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.2% |
