Margot Dupre for NC US Inactive
MARGOT DUPRE FOR US SENATE
Ad copy
Between attending the g*n show near Asheville and attending services led by Pastor Jack in Black Mountain, I had the chance to explore The Bee Tree area of Swannanoa and Longbranch. I had hoped that these communities had received the help they needed and deserved. Sadly, they have not. While Michael Watley travels the country and hangs out at the Texas border to talk about immigration, I’m here trying to figure out how to fix the disaster he has ignored and left behind. I am here now. I’ll be here when you elect me. Please vote for Margot Dupre for US Senate NC 2026.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 31.4/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 53.0 · 0.3 · 72.5 |
| Spend range | <USD 99 |
| Impressions | 9,000 – 9,999 |
| CPM (≈ $/1k impr) | USD 5.21 |
| Est. audience size | — |
| Days live | 2 (2026-01-12 → 2026-01-14) |
| Created | 2026-01-11 |
| Creative variants | 1 body · 0 headline |
| Platforms | |
| Languages | en |
| Candidate | NC — Margot Dupre |
| Surfaced by | “senate:Margot Dupre” |
🧠 AI analysis
| Issue | crime safety |
| Framing | contrast comparison |
| Message type | persuasion |
| Emotional appeal | empathy |
| Production tier | diy amateur |
| Who pictured | none |
| Symbols | farm rural |
| Call to action | vote |
| Standout element | Unrestored storm-damaged rural landscape photos contrasting opponent's absence from the community |
| Tactic | The ad uses a presence-vs-absence contrast tactic, positioning Dupre as a boots-on-the-ground candidate actively witnessing neglected disaster recovery while attacking opponent Watley for being distracted by immigration politics at the Texas border. |
Where it ran (delivery by region)
| North Carolina | 100.0% |
Who saw it (delivery)
| 18-24 · female | 1.0% |
| 45-54 · male | 12.8% |
| 65+ · male | 8.4% |
| 65+ · female | 4.3% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 10.6% |
| 55-64 · female | 3.1% |
| 45-54 · unknown | 0.0% |
| 45-54 · female | 3.6% |
| 18-24 · male | 4.6% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 19.8% |
| 35-44 · female | 5.1% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 22.4% |
| 25-34 · female | 3.9% |
| 65+ · unknown | 0.0% |
