Chris Pappas US Inactive
Chris Pappas for Senate
🚨Tied Race Alert: Donate
Show your support with a contribution.
Ad copy
Hey folks, it’s Chris Pappas with an important update on this race: I’m tied with my opponent in multiple polls. It’s another reason why New Hampshire’s Senate race will be one of the most competitive — and expensive — races on the map this year. National Republicans and their dark money allies are ready to do whatever it takes to flip this seat. I’ve won tough races before, so I know this to be true: The way to win a race this close is with a strong grassroots team. If we’re going to have a chance to flip the Senate, I need you by my side in New Hampshire. Can I count on you to chip in today to help us keep up the fight?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 38.4/100 |
| Spend / Reach / Long. / Eff. | 27.6 · 55.8 · 14.9 · 55.4 |
| Spend range | USD 600–699 |
| Impressions | 10,000 – 14,999 |
| CPM (≈ $/1k impr) | USD 51.96 |
| Est. audience size | — |
| Days live | 55 (2026-01-13 → 2026-03-09) |
| Created | 2026-01-13 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | NH — Chris Pappas |
| Surfaced by | “senate:Chris Pappas” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate, opponent |
| Symbols | none |
| Call to action | donate |
| Standout element | Side-by-side candidate comparison with red-tinted opponent photo versus clean blue candidate photo and polling margin graphic |
| Tactic | Uses a tied-poll alarm to manufacture urgency, framing the close race as a call-to-action that only a grassroots donation surge can answer. |
Where it ran (delivery by region)
| New York | 47.2% |
| Massachusetts | 30.7% |
| California | 22.1% |
Who saw it (delivery)
| 18-24 · female | 0.1% |
| 45-54 · male | 2.9% |
| 65+ · male | 32.3% |
| 65+ · female | 36.4% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 8.9% |
| 55-64 · female | 10.2% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 3.3% |
| 18-24 · male | 0.1% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 1.5% |
| 35-44 · female | 1.6% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 0.8% |
| 25-34 · female | 0.7% |
| 65+ · unknown | 1.0% |
