Haley Stevens US Inactive
Haley Stevens for Congress
🔴 All donations will be MATCHED!
Double your impact and defend our Majority >>
Ad copy
Donald Trump personally tried to recruit a Republican to challenge me. He knows he carried this district by four points in 2016 and he knows if Frontline Democrats like me lose in 2020, Republicans will retake the House. We can't let that happen. So I'm asking if you will rush in a MATCHED donation before the end of the month toward my FEC End of Quarter goal so we can win this race and defend our Majority.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 37.6/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 59.2 · 2.5 · 50.5 |
| Spend range | USD 1,500–1,999 |
| Impressions | 15,000 – 19,999 |
| CPM (≈ $/1k impr) | USD 99.97 |
| Est. audience size | — |
| Days live | 10 (2019-06-20 → 2019-06-30) |
| Created | 2019-06-20 |
| Creative variants | 1 body · 1 headline |
| Platforms | — |
| Languages | en |
| Candidate | MI — Haley Stevens |
| Surfaced by | “senate:Haley Stevens” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | unknown |
| Who pictured | none |
| Symbols | none |
| Call to action | donate |
| Standout element | Blank/unloaded image with urgency entirely carried by copy alone |
| Tactic | The ad leverages Trump as a direct antagonist to create a personal stakes narrative, pairing a matched-donation deadline with a majority-defense frame to maximize end-of-quarter urgency giving. |
Where it ran (delivery by region)
| Michigan | 21.1% |
| California | 10.8% |
| New York | 7.0% |
| Illinois | 4.9% |
| Massachusetts | 4.2% |
| Florida | 4.1% |
| Texas | 3.8% |
Who saw it (delivery)
| 18-24 · unknown | 0.0% |
| 25-34 · male | 1.9% |
| 35-44 · unknown | 0.2% |
| 18-24 · male | 0.4% |
| 25-34 · unknown | 0.1% |
| 55-64 · unknown | 0.2% |
| 25-34 · female | 2.1% |
| 45-54 · female | 8.2% |
| 35-44 · female | 5.0% |
| 35-44 · male | 3.1% |
| 18-24 · female | 0.5% |
| 55-64 · male | 6.4% |
| 65+ · male | 12.8% |
| 65+ · unknown | 0.7% |
| 45-54 · male | 3.8% |
| 55-64 · female | 17.0% |
| 65+ · female | 37.5% |
| 45-54 · unknown | 0.2% |
