Haley Stevens US Inactive
HALEY STEVENS FOR CONGRESS
Re-Elect Haley Stevens to Congress
Ad copy
Haley Stevens has fought for manufacturing jobs in Michigan and won. She’s kept her promises on promoting STEM education and expanding healthcare coverage to Michiganders who need it. Haley is Michigan tough, and this district knows it. Vote to re-elect Haley Stevens to Congress.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 58.3/100 |
| Spend / Reach / Long. / Eff. | 63.0 · 97.1 · 11.8 · 61.3 |
| Spend range | USD 15,000–19,999 |
| Impressions | 700,000 – 799,999 |
| CPM (≈ $/1k impr) | USD 23.33 |
| Est. audience size | 50,001 – 100,000 |
| Days live | 44 (2020-09-08 → 2020-10-22) |
| Created | 2020-09-08 |
| 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 | vote |
| Standout element | Bold red-and-white 'TAKING ON CHINA' headline overlaid on a dark factory floor setting with the candidate |
| Tactic | The ad uses an aggressive, nationalistic trade frame ('Taking on China') paired with a factory backdrop to position Stevens as a tough, results-driven fighter for Michigan manufacturing workers, blending economic patriotism with a proven-record appeal. |
Where it ran (delivery by region)
| Michigan | 100.0% |
Who saw it (delivery)
| 18-24 · unknown | 0.1% |
| 25-34 · female | 12.6% |
| 65+ · unknown | 0.1% |
| 45-54 · female | 12.2% |
| 45-54 · male | 7.4% |
| 35-44 · female | 12.8% |
| 55-64 · male | 5.4% |
| 55-64 · female | 8.7% |
| 65+ · male | 3.5% |
| 45-54 · unknown | 0.2% |
| 25-34 · male | 9.3% |
| 35-44 · male | 8.9% |
| 18-24 · female | 7.3% |
| 25-34 · unknown | 0.1% |
| 18-24 · male | 5.1% |
| 65+ · female | 6.1% |
| 35-44 · unknown | 0.2% |
| 55-64 · unknown | 0.1% |
