PHILLIP RENCH FOR US SENATE CAMPAIGN
Hey Folks, We need new industries in Maine and to reinvent existing ones. Decades ago, Maine was a leader in lumber production, producing over 1 billion board feet a year; however…
Hey Folks, We need new industries in Maine and to reinvent existing ones. Decades ago, Maine was a leader in lumber production, producing over 1 billion board feet a year; however, due to competition from subsidized industries in Canada, that number has shrunk to just 400 million. The folks I have spoken with in Northern Maine want these jobs back, and I have a plan to make it happen. Learn more here: https://phillipformaine.com/strategic-lumber-reserve/
↗ View in Meta Ad Library (the live creative — image/video/layout)
| Overall score | 23.3/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 34.4 · 0.0 · 58.7 |
| Spend range | <USD 99 |
| Impressions | 1,000 – 1,999 |
| CPM (≈ $/1k impr) | USD 33.01 |
| Est. audience size | — |
| Days live | 1 (2025-08-07 → 2025-08-08) |
| Created | 2025-08-07 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Phillip Rench |
| Surfaced by | “senate:Phillip Rench” |
| Issue | agriculture rural |
| Framing | issue advocacy |
| Message type | persuasion |
| Emotional appeal | nostalgia |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | farm rural, factory industry |
| Call to action | learn more |
| Standout element | Badge-style illustrated logo with pine trees and stacked logs evoking a classic heritage brand identity for Maine lumber |
| Tactic | The ad uses economic nostalgia and concrete statistics (1 billion vs. 400 million board feet) to frame Canadian subsidies as the villain and position the candidate as a pro-jobs economic revivalist with a credible plan. |
| Maine | 52.4% |
| Massachusetts | 3.8% |
| Connecticut | 3.7% |
| New York | 3.5% |
| New Hampshire | 2.9% |
| Florida | 2.3% |
| Michigan | 2.3% |
| 18-24 · female | 0.1% |
| 18-24 · male | 0.3% |
| 25-34 · female | 0.3% |
| 25-34 · male | 4.0% |
| 35-44 · female | 0.4% |
| 35-44 · male | 9.2% |
| 35-44 · unknown | 0.1% |
| 45-54 · female | 1.0% |
| 45-54 · male | 14.1% |
| 45-54 · unknown | 0.2% |
| 55-64 · female | 2.6% |
| 55-64 · male | 23.6% |
| 55-64 · unknown | 0.3% |
| 65+ · female | 6.7% |
| 65+ · male | 36.8% |
| 65+ · unknown | 0.4% |