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 | 43.2/100 |
| Spend / Reach / Long. / Eff. | 31.7 · 59.2 · 26.7 · 55.0 |
| Spend range | USD 900–999 |
| Impressions | 15,000 – 19,999 |
| CPM (≈ $/1k impr) | USD 54.26 |
| Est. audience size | — |
| Days live | 98 (2019-11-05 → 2020-02-11) |
| Created | 2019-11-04 |
| 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 | Green 'YOU'VE BEEN SELECTED' banner over Shaheen's smiling photo creating a personalized urgency trigger |
| Tactic | Classic fundraising urgency tactic combining a named-threat (Trump recruiting Lewandowski) with a midnight match deadline and personalized 'top Democrat' flattery to maximize donation conversion. |
| California | 15.3% |
| New York | 10.7% |
| Massachusetts | 6.3% |
| Florida | 5.7% |
| Pennsylvania | 4.3% |
| Washington | 4.3% |
| New Jersey | 3.4% |
| 35-44 · unknown | 0.0% |
| 45-54 · male | 4.2% |
| 55-64 · male | 11.3% |
| 55-64 · female | 18.8% |
| 65+ · female | 34.1% |
| 65+ · unknown | 0.9% |
| 35-44 · female | 1.1% |
| 65+ · male | 22.2% |
| 45-54 · female | 5.2% |
| 35-44 · male | 1.2% |
| 55-64 · unknown | 0.6% |
| 45-54 · unknown | 0.2% |