Reilly Neill for U.S. Senate US Inactive
REILLY FOR MONTANA
A Call on Our Water
When it comes to data centers, Montanans deserve clear answers.
Ad copy
A data center near Butte uses as much electricity as the city of Helena, #Montana. The Quantica Center near Billings is poised to use more electricity than the entire state of Montana. Who carries the cost? Who reaps the benefit? https://reillyneill.substack.com/p/a-call-on-our-water
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 30.0/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 49.2 · 1.1 · 69.7 |
| Spend range | <USD 99 |
| Impressions | 6,000 – 6,999 |
| CPM (≈ $/1k impr) | USD 7.62 |
| Est. audience size | — |
| Days live | 5 (2025-12-27 → 2026-01-01) |
| Created | 2025-12-27 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MT — Reilly Neill |
| Surfaced by | “senate:Reilly Neill” |
🧠 AI analysis
| Issue | energy environment |
| Framing | issue advocacy |
| Message type | awareness |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | farm rural |
| Call to action | learn more |
| Standout element | Lonely weathered dock structure on a frozen Montana lake evoking the fragility of local resources |
| Tactic | The ad uses a rhetorical 'who pays / who benefits' framing to stoke populist concern over out-of-state tech corporations exploiting Montana's energy grid and water, driving readers to a Substack deep-dive for credibility. |
Where it ran (delivery by region)
| Montana | 10.1% |
| California | 6.3% |
| Washington | 5.8% |
| Michigan | 5.0% |
| Florida | 4.5% |
| Oregon | 4.1% |
| Wisconsin | 3.8% |
Who saw it (delivery)
| 18-24 · female | 0.1% |
| 45-54 · male | 2.6% |
| 65+ · male | 32.9% |
| 65+ · female | 39.6% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 8.2% |
| 55-64 · female | 9.1% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 2.5% |
| 18-24 · male | 0.0% |
| 35-44 · unknown | 0.0% |
| 35-44 · male | 1.5% |
| 35-44 · female | 1.1% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 0.5% |
| 25-34 · female | 0.6% |
| 65+ · unknown | 0.8% |
