Mallory McMorrow US Inactive
Mallory McMorrow for Michigan
Donate to Mallory McMorrow for U.S. Senate
Ad copy
Democratic control of the US Senate depends on what we do right now in Michigan. And make no mistake, this will be one of the closest and most expensive races in the entire country. MAGA billionaires are already lining up to support Mike Rogers and Trump is ALL IN on flipping this seat. Polls show we can win. In fact, we’re leading Rogers in the latest poll. But that only matters if we can sustain our momentum through the attack ads coming our way. So I’m asking if you can make a donation to make sure we have the resources to compete and win.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 59.6/100 |
| Spend / Reach / Long. / Eff. | 78.6 · 97.1 · 12.1 · 50.5 |
| Spend range | USD 70,000–79,999 |
| Impressions | 700,000 – 799,999 |
| CPM (≈ $/1k impr) | USD 100.0 |
| Est. audience size | — |
| Days live | 45 (2026-02-17 → 2026-04-03) |
| Created | 2026-02-17 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MI — Mallory Mcmorrow |
| Surfaced by | “senate:Mallory Mcmorrow” |
🧠 AI analysis
| 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 | Candidate filmed casually at a laptop in a cozy sweater, projecting authenticity over polish |
| Tactic | The ad uses an urgency-driven fundraising appeal anchored in poll momentum and a billionaire-threat frame to convert grassroots supporters into donors before attack ads hit. |
Where it ran (delivery by region)
| California | 14.5% |
| New York | 7.0% |
| Florida | 6.6% |
| Michigan | 6.4% |
| Massachusetts | 4.2% |
| Washington | 4.0% |
| Texas | 3.9% |
Who saw it (delivery)
| 18-24 · female | 0.1% |
| 45-54 · unknown | 0.1% |
| Unknown · male | 0.0% |
| Unknown · female | 0.0% |
| 65+ · unknown | 0.8% |
| 65+ · male | 23.8% |
| 65+ · female | 43.9% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 6.4% |
| 55-64 · female | 12.8% |
| 45-54 · male | 2.2% |
| 18-24 · male | 0.1% |
| 45-54 · female | 4.4% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 1.3% |
| 35-44 · female | 2.2% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 0.6% |
| 25-34 · female | 1.0% |
| 18-24 · unknown | 0.0% |
| Unknown · unknown | 0.0% |
