Tom Willis WV US Inactive
Friends of Tom Willis
Ad copy
Over the past year, Craig Blair has- Rammed through giving $290 MILLION of your tax dollars to Left Radical Bill Gates to bring his woke ideas to West Virginia. Pushed through Legislation to allow ‘Green New Deal’ bureaucrats to have power over your elected officials. Refused to allow a vote on the West Virginia First Act which would stop your money from going to out-of-state Left Wing radicals.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 40.9/100 |
| Spend / Reach / Long. / Eff. | 21.0 · 61.7 · 16.3 · 64.4 |
| Spend range | USD 300–399 |
| Impressions | 20,000 – 24,999 |
| CPM (≈ $/1k impr) | USD 15.53 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 60 (2024-03-12 → 2024-05-11) |
| Created | 2024-03-12 |
| Creative variants | 1 body · 0 headline |
| Platforms | |
| Languages | en |
| Candidate | WV — Tom Willis |
| Surfaced by | “senate:Tom Willis” |
🧠 AI analysis
| Issue | energy environment |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | opponent |
| Symbols | money cash, none |
| Call to action | none |
| Standout element | Composite image placing Craig Blair at a podium flanked by Barack Obama and Bill Gates against a wind farm backdrop with 'Green New Deal Network' branding |
| Tactic | The ad uses guilt-by-association imagery — literally placing the opponent between nationally polarizing liberal figures — to trigger cultural and financial resentment among conservative West Virginia voters. |
Where it ran (delivery by region)
| West Virginia | 81.4% |
| Maryland | 16.9% |
| Virginia | 1.7% |
| Unknown | 0.0% |
Who saw it (delivery)
| 25-34 · unknown | 0.0% |
| 55-64 · unknown | 0.2% |
| 25-34 · male | 1.1% |
| 35-44 · unknown | 0.1% |
| 45-54 · female | 3.9% |
| 65+ · female | 22.4% |
| 35-44 · male | 4.8% |
| 55-64 · male | 18.6% |
| 35-44 · female | 1.5% |
| 55-64 · female | 10.2% |
| 65+ · male | 26.2% |
| 45-54 · male | 10.4% |
| 45-54 · unknown | 0.1% |
| 25-34 · female | 0.3% |
| 65+ · unknown | 0.2% |
