Haley Stevens US Inactive
HALEY STEVENS FOR CONGRESS
MI-11 and Our Democratic Majority Are ON THE LINE [DONATE $10]
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Ad copy
THIS ISN’T GOOD: Michigan’s 11th is in DANGER of flipping red in 2022. We’re facing a historic election in this battleground district, and the margin is RAZOR THIN. A FLOOD of spending is coming in from the national Republican war chest. Will you rush a $5 donation to protect the progress we’ve made in MI-11? This is one of the tightest seats in the country. Help re-elect Michigan’s champion and defend our majority with a donation.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 37.9/100 |
| Spend / Reach / Long. / Eff. | 31.7 · 59.2 · 5.8 · 55.0 |
| Spend range | USD 900–999 |
| Impressions | 15,000 – 19,999 |
| CPM (≈ $/1k impr) | USD 54.26 |
| Est. audience size | — |
| Days live | 22 (2021-05-05 → 2021-05-27) |
| Created | 2021-05-05 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MI — Haley Stevens |
| Surfaced by | “senate:Haley Stevens” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Candidate posed arms-crossed against a billboard-style threat warning in bold orange and white type |
| Tactic | Classic fear-based fundraising tactic using urgency and victimhood framing — positioning the candidate as a top Republican target to trigger small-dollar donor response. |
Where it ran (delivery by region)
| California | 14.4% |
| Michigan | 10.0% |
| New York | 6.3% |
| Pennsylvania | 6.2% |
| Florida | 5.8% |
| Washington | 4.3% |
| Illinois | 3.8% |
Who saw it (delivery)
| 25-34 · unknown | 0.1% |
| 65+ · male | 33.7% |
| 65+ · unknown | 0.8% |
| 18-24 · female | 0.2% |
| 55-64 · male | 11.9% |
| 45-54 · male | 4.0% |
| 25-34 · female | 0.6% |
| 65+ · female | 32.1% |
| 55-64 · female | 9.0% |
| 18-24 · unknown | 0.0% |
| 45-54 · female | 2.4% |
| 35-44 · male | 2.1% |
| 35-44 · female | 1.0% |
| 18-24 · male | 0.3% |
| 25-34 · male | 1.2% |
| 35-44 · unknown | 0.1% |
| 45-54 · unknown | 0.1% |
| 55-64 · unknown | 0.4% |
