Paul Dans for US Senate US Inactive
PAUL DANS FOR SENATE
Ad copy
I am Paul Dans. I'm a Father of 4 who worked for Dr. Ben Carson during Donald Trump's first term in office. I recently visited Conway to investigate the flooding problems, and there is a very simple solution. BUILD A CANAL that moves the water coming down from North Carolina into the Waccamaw River then out into the ocean. We need a US Senator who will get all of the Low Country the money it deserves and STOP THE FLOODING and make farming possible again. Watch me explain my proposal below. Visit PaulDans.com to learn more.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 46.1/100 |
| Spend / Reach / Long. / Eff. | 44.9 · 73.9 · 8.8 · 56.7 |
| Spend range | USD 3,000–3,499 |
| Impressions | 70,000 – 79,999 |
| CPM (≈ $/1k impr) | USD 43.33 |
| Est. audience size | 500,001 – 1,000,000 |
| Days live | 33 (2026-03-06 → 2026-04-08) |
| Created | 2026-03-06 |
| Creative variants | 1 body · 0 headline |
| Platforms | |
| Languages | en |
| Candidate | SC — Paul Dans |
| Surfaced by | “senate:Paul Dans” |
🧠 AI analysis
| Issue | energy environment |
| Framing | issue advocacy |
| Message type | persuasion |
| Emotional appeal | urgency |
| Production tier | diy amateur |
| Who pictured | none |
| Symbols | farm rural |
| Call to action | vote |
| Standout element | Flooded landscape with bare trees standing in water, visually demonstrating the flooding crisis the candidate promises to solve |
| Tactic | The ad uses authentic on-location footage of actual flooding to lend credibility to the candidate's specific infrastructure proposal, positioning Dans as a hands-on problem-solver who personally investigates local issues. |
Where it ran (delivery by region)
| South Carolina | 85.4% |
| North Carolina | 14.6% |
Who saw it (delivery)
| 18-24 · female | 0.2% |
| 45-54 · male | 13.9% |
| 65+ · male | 16.2% |
| 65+ · female | 9.9% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 17.7% |
| 55-64 · female | 8.3% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 4.8% |
| 18-24 · male | 1.6% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 13.1% |
| 35-44 · female | 3.4% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 8.6% |
| 25-34 · female | 1.5% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.2% |
