Tom Willis WV US Inactive
Tom Willis Victory
Tom Willis - US Senate
Ad copy
Do you support gun confiscation without due process? Should your tax dollars fund Planned Parenthood? Do you think men belong in women’s sports? If you said NO — you’re not alone. I am standing up to the D.C. swamp and taking our values back. Watch my campaign announcement video now and join the fight Capito turned her back on West Virginia. Now it’s our turn to stand up — for faith, family, freedom, and the Constitution. Share this video. Spread the word. The fight is on. #TomWillisForSenate #WVValues #NoMoreRINOs #StandWithTom
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 41.8/100 |
| Spend / Reach / Long. / Eff. | 23.7 · 72.4 · 0.6 · 70.4 |
| Spend range | USD 400–499 |
| Impressions | 60,000 – 69,999 |
| CPM (≈ $/1k impr) | USD 6.92 |
| Est. audience size | 500,001 – 1,000,000 |
| Days live | 3 (2025-07-30 → 2025-08-02) |
| Created | 2025-07-29 |
| Creative variants | 1 body · 1 headline |
| Platforms | |
| Languages | en |
| Candidate | WV — Tom Willis |
| Surfaced by | “senate:Tom Willis” |
🧠 AI analysis
| Issue | guns |
| Framing | positive candidate |
| Message type | list building survey |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | guns 2a, family |
| Call to action | learn more |
| Standout element | Three rapid-fire rhetorical questions designed to trigger ideological alignment before the candidate self-introduction |
| Tactic | Classic push-poll list-building tactic — stacking three hot-button conservative litmus-test questions to qualify the audience and create psychological momentum before the ask, then pivoting to anti-establishment 'RINO' contrast to drive list sign-ups and video views. |
Where it ran (delivery by region)
| West Virginia | 100.0% |
| Unknown | 0.0% |
Who saw it (delivery)
| 18-24 · female | 0.0% |
| 45-54 · male | 13.3% |
| 65+ · male | 20.7% |
| 65+ · female | 17.7% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 18.4% |
| 55-64 · female | 10.8% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 5.7% |
| 18-24 · male | 0.1% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 7.3% |
| 35-44 · female | 2.6% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 2.2% |
| 25-34 · female | 0.7% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.2% |
