Shaheen for Senate
Every dollar DOUBLED to win in NH and take back the Senate for Democrats.
BREAKING: President Trump is personally recruiting his former campaign manager Corey Lewandowski to run for Senate in New Hampshire. He knows that Democrats CANNOT take back the Senate if we lose in New Hampshire, so he and the GOP are ALL IN to defeat me and keep a Republican Senate majority. That’s why a group of donors will MATCH ALL GIFTS to help us defend New Hampshire’s Democratic Senate seat – but we’re still $2,174 short and have to close the gap before 11:59 p.m. tonight. Donate now and have your gift DOUBLED to stop Trump and Lewandowski and take back the Senate!
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| Overall score | 46.3/100 |
| Spend / Reach / Long. / Eff. | 49.0 · 72.4 · 11.0 · 52.8 |
| Spend range | USD 4,500–4,999 |
| Impressions | 60,000 – 69,999 |
| CPM (≈ $/1k impr) | USD 73.07 |
| Est. audience size | — |
| Days live | 41 (2019-09-25 → 2019-11-05) |
| Created | 2019-09-24 |
| Creative variants | 1 body · 1 headline |
| Platforms | — |
| Languages | en |
| Candidate | NH — Jeanne Shaheen |
| Surfaced by | “senate:Jeanne Shaheen” |
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Bright green DONATE button paired with midnight deadline urgency bar driving immediate action |
| Tactic | Classic fear-and-urgency fundraising tactic: names a threatening opponent (Trump/Lewandowski), invokes a matching gift deadline, and frames donation as the direct antidote to losing the Senate majority. |
| California | 14.0% |
| New York | 9.7% |
| Massachusetts | 7.2% |
| Florida | 4.8% |
| Washington | 4.5% |
| Pennsylvania | 4.3% |
| New Jersey | 3.5% |
| 65+ · female | 40.6% |
| 55-64 · female | 21.3% |
| 65+ · male | 16.2% |
| 45-54 · female | 5.9% |
| 45-54 · male | 3.1% |
| 55-64 · male | 9.3% |
| 35-44 · male | 0.7% |
| 65+ · unknown | 0.9% |
| 55-64 · unknown | 0.5% |
| 35-44 · female | 1.2% |
| 35-44 · unknown | 0.1% |
| 45-54 · unknown | 0.2% |