Phillip Rench for Maine US Inactive
PHILLIP RENCH FOR US SENATE CAMPAIGN
About
My name is Phillip Rench, I am a husband and father of two young children living in Waterboro, Maine where I grew up as a child. My passion has always been engineering and space…
Ad copy
The National Debt is about to hit 37 Trillion Dollars. Prior to Senator Collins joining the appropriations committee in 2009, it was just shy of 12 Trillion. She is not solely to blame for this debt, but she has failed to perform her fiscal oversight responsibilities and has yet to balance a budget. Can you guess what will happen to this graph if Senator Collins is elected another 6 years? We need fiscal responsibility in Washington. It’s time to cut up Senator Collins’s ‘credit card’ before she maxes out America.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 31.2/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 51.9 · 1.1 · 71.7 |
| Spend range | <USD 99 |
| Impressions | 8,000 – 8,999 |
| CPM (≈ $/1k impr) | USD 5.82 |
| Est. audience size | — |
| Days live | 5 (2025-08-12 → 2025-08-17) |
| Created | 2025-08-11 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Phillip Rench |
| Surfaced by | “senate:Phillip Rench” |
🧠 AI analysis
| Issue | economy taxes |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | money cash |
| Call to action | learn more |
| Standout element | sharply rising national debt line chart anchored to Collins joining the Appropriations Committee in 2009 |
| Tactic | The ad uses a data-driven guilt-by-association tactic, visually correlating Collins's tenure on the Appropriations Committee with skyrocketing national debt to imply personal culpability and argue for her removal. |
Where it ran (delivery by region)
| Maine | 100.0% |
Who saw it (delivery)
| 18-24 · female | 0.0% |
| 45-54 · male | 9.2% |
| 65+ · male | 14.3% |
| 65+ · female | 15.7% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 10.6% |
| 55-64 · female | 11.0% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 6.3% |
| 18-24 · male | 0.2% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 17.5% |
| 35-44 · female | 6.7% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 5.8% |
| 25-34 · female | 1.3% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.4% |
