Haley Stevens US Inactive
HALEY STEVENS FOR CONGRESS
Haley Stevens — Bringing American Jobs Back
Ad copy
Manufacturing in Michigan just got a boost thanks to Congresswoman Haley Stevens. Haley Stevens worked across party lines to manufacture microchips in America. Not factories in China.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 49.5/100 |
| Spend / Reach / Long. / Eff. | 55.2 · 81.7 · 5.8 · 55.3 |
| Spend range | USD 8,000–8,999 |
| Impressions | 150,000 – 174,999 |
| CPM (≈ $/1k impr) | USD 52.3 |
| Est. audience size | 10,001 – 50,000 |
| Days live | 22 (2022-10-14 → 2022-11-05) |
| Created | 2022-10-14 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MI — Haley Stevens |
| Surfaced by | “senate:Haley Stevens” |
🧠 AI analysis
| Issue | jobs labor |
| Framing | positive candidate |
| Message type | persuasion |
| Emotional appeal | pride |
| Production tier | professional |
| Who pictured | candidate, workers labor |
| Symbols | factory industry |
| Call to action | learn more |
| Standout element | Candidate shown hands-on at a manufacturing workstation alongside a worker, visually proving her engagement with industry |
| Tactic | The ad uses a 'working candidate' visual paired with a bipartisan credibility claim and an implicit China contrast to appeal to economic nationalism without going overtly negative. |
Where it ran (delivery by region)
| Michigan | 99.9% |
| Florida | 0.0% |
| Ohio | 0.0% |
| North Carolina | 0.0% |
| Texas | 0.0% |
| California | 0.0% |
| New Jersey | 0.0% |
Who saw it (delivery)
| 18-24 · unknown | 0.0% |
| 45-54 · male | 7.2% |
| 13-17 · female | 0.0% |
| 25-34 · unknown | 0.1% |
| 45-54 · unknown | 0.2% |
| 35-44 · female | 15.7% |
| 65+ · female | 13.7% |
| 55-64 · female | 12.9% |
| 25-34 · male | 5.1% |
| 25-34 · female | 7.7% |
| 65+ · unknown | 0.2% |
| 35-44 · male | 9.1% |
| 45-54 · female | 15.3% |
| 55-64 · male | 5.3% |
| 18-24 · male | 0.7% |
| 65+ · male | 5.6% |
| 18-24 · female | 0.7% |
| 55-64 · unknown | 0.2% |
| 35-44 · unknown | 0.3% |
| 13-17 · male | 0.0% |
