Mallory McMorrow for Michigan
As you read this, Republicans are spending millions of dollars to flip Michigan. Donald Trump, the DeVos family, the Koch network, and MAGA billionaires are all in on trying to buy this seat. We need your help to respond. Will you make a donation today, right now, to ensure we have the resources to fight back against whatever the Trump administration will throw at us?
As you read this, Republicans are spending millions of dollars to flip Michigan. Donald Trump, the DeVos family, the Koch network, and MAGA billionaires are all in on trying to buy this seat. We need your help to respond. Will you make a donation today, right now, to ensure we have the resources to fight back against whatever the Trump administration will throw at us?
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| Overall score | 44.4/100 |
| Spend / Reach / Long. / Eff. | 46.5 · 68.1 · 11.6 · 51.4 |
| Spend range | USD 3,500–3,999 |
| Impressions | 40,000 – 44,999 |
| CPM (≈ $/1k impr) | USD 88.22 |
| Est. audience size | 50,001 – 100,000 |
| Days live | 43 (2026-04-23 → 2026-06-05) |
| Created | 2026-04-22 |
| Creative variants | 2 body · 2 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MI — Mallory Mcmorrow |
| Surfaced by | “senate:Mallory Mcmorrow” |
| Issue | democracy elections |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Candidate speaking directly to camera with hands raised in an urgent explanatory gesture against her own campaign backdrop, creating an intimate direct-appeal feel |
| Tactic | Classic fear-and-urgency fundraising tactic that names specific high-profile Republican donors to make the threat concrete and motivate immediate financial response. |
| Michigan | 28.2% |
| California | 11.1% |
| New York | 4.8% |
| Florida | 4.6% |
| Illinois | 4.0% |
| Texas | 3.2% |
| Washington | 3.1% |
| 18-24 · female | 0.2% |
| 45-54 · male | 3.8% |
| 65+ · male | 35.7% |
| 65+ · female | 31.0% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 9.5% |
| 55-64 · female | 8.5% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 3.1% |
| 18-24 · male | 0.2% |
| 35-44 · unknown | 0.0% |
| 35-44 · male | 2.3% |
| 35-44 · female | 1.9% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 1.6% |
| 25-34 · female | 1.0% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.7% |