Reilly Neill for U.S. Senate US Inactive
REILLY FOR MONTANA
Ad copy
The people should know. Every single mailer, every single commercial built with AI is an effort to sell Montanans data centers in a tidy package. We won’t buy it. Take your millions in dirty data center money and shove it where the sun don’t shine. #ReillyforMontana Read more: https://reillyneill.substack.com/p/a-billion-dollars-wont-buy-consent
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 30.4/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 50.6 · 0.3 · 70.8 |
| Spend range | <USD 99 |
| Impressions | 7,000 – 7,999 |
| CPM (≈ $/1k impr) | USD 6.6 |
| Est. audience size | — |
| Days live | 2 (2026-06-01 → 2026-06-03) |
| Created | 2026-06-01 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MT — Reilly Neill |
| Surfaced by | “senate:Reilly Neill” |
🧠 AI analysis
| Issue | energy environment |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | farm rural, money cash |
| Call to action | learn more |
| Standout element | Dramatic stormy Montana sky with rays breaking through clouds juxtaposed against defiant populist headline |
| Tactic | The ad uses grassroots outrage and populist anti-corporate framing to position the candidate as a defender of Montana sovereignty against big-money AI/data center interests, leveraging raw unpolished language to signal authenticity. |
Where it ran (delivery by region)
| Arizona | 23.0% |
| Washington | 18.6% |
| Colorado | 13.5% |
| Oregon | 11.1% |
| Nevada | 6.3% |
| Montana | 6.3% |
| Utah | 4.1% |
Who saw it (delivery)
| 18-24 · female | 0.1% |
| 45-54 · male | 4.1% |
| 65+ · male | 19.3% |
| 65+ · female | 36.6% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 7.6% |
| 55-64 · female | 13.1% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 6.2% |
| 18-24 · male | 0.2% |
| 35-44 · unknown | 0.3% |
| 35-44 · male | 3.6% |
| 35-44 · female | 4.3% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 1.4% |
| 25-34 · female | 1.8% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.7% |
