Chris Pappas for Senate
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🚨BREAKING: Multiple polls show our campaign TIED with John Sununu. 🚨 National Republicans and their dark money allies already see this as one of their best chances to flip a Senate seat. If they take New Hampshire, Democrats have no shot at winning back the majority. This race is way too close for comfort. But we’ve won tough races before – with the support of a strong grassroots movement of people like you. Will you chip in $5, $10, or whatever you can today to defend this Senate seat? Let’s fight with everything we have to hold New Hampshire and help Democrats win control of the Senate to provide a check in Washington.
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| Overall score | 37.6/100 |
| Spend / Reach / Long. / Eff. | 25.8 · 55.8 · 12.1 · 56.6 |
| Spend range | USD 500–599 |
| Impressions | 10,000 – 14,999 |
| CPM (≈ $/1k impr) | USD 43.96 |
| Est. audience size | — |
| Days live | 45 (2026-01-13 → 2026-02-27) |
| Created | 2026-01-13 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | NH — Chris Pappas |
| Surfaced by | “senate:Chris Pappas” |
| 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 Sununu in ominous red-tinted photo vs. Pappas in clean blue, marked with an X and a checkmark respectively |
| Tactic | Classic tied-race urgency fundraising tactic using polling data and dark-money threat framing to manufacture FOMO and drive small-dollar donations. |
| New Hampshire | 22.3% |
| California | 9.1% |
| Massachusetts | 7.5% |
| Florida | 5.8% |
| New York | 5.0% |
| Maine | 4.6% |
| Washington | 3.8% |
| 18-24 · female | 0.1% |
| 45-54 · male | 2.6% |
| 65+ · male | 27.2% |
| 65+ · female | 39.4% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 6.9% |
| 55-64 · female | 9.7% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 4.1% |
| 18-24 · male | 0.1% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 2.3% |
| 35-44 · female | 3.7% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 1.1% |
| 25-34 · female | 1.6% |
| 65+ · unknown | 0.8% |