Sherrod Brown US Inactive
FRIENDS OF SHERROD BROWN
Ohio Workers Can’t Trust Moreno
Ohio Workers Can’t Trust Moreno
Ohio Workers Can’t Trust Moreno
Ohio Workers Can’t Trust Moreno
Ad copy
Car salesman Bernie Moreno made a fortune selling Chinese-made cars while Ohio workers were losing their jobs.
Car salesman Bernie Moreno made a fortune selling Chinese-made cars while Ohio workers were losing their jobs.
Car salesman Bernie Moreno made a fortune selling Chinese-made cars while Ohio workers were losing their jobs.
Car salesman Bernie Moreno made a fortune selling Chinese-made cars while Ohio workers were losing their jobs.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 55.0/100 |
| Spend / Reach / Long. / Eff. | 50.6 · 94.0 · 7.7 · 67.7 |
| Spend range | USD 5,000–5,999 |
| Impressions | 500,000 – 599,999 |
| CPM (≈ $/1k impr) | USD 10.0 |
| Est. audience size | 500,001 – 1,000,000 |
| Days live | 29 (2024-06-14 → 2024-07-13) |
| Created | 2024-06-14 |
| Creative variants | 4 body · 4 headline |
| Platforms | facebook, instagram |
| Languages | — |
| Candidate | OH — Sherrod Brown |
| Surfaced by | “senate:Sherrod Brown” |
🧠 AI analysis
| Issue | jobs labor |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | workers labor |
| Symbols | factory industry, money cash |
| Call to action | learn more |
| Standout element | Dark, bleak video frame of a depressed Ohio street overlaid with a real WEWS news headline about GM Lordstown plant closure |
| Tactic | The ad weaponizes a real local news broadcast about devastating factory job losses to implicitly blame Moreno for profiting from Chinese car sales while Ohio workers suffered, using borrowed credibility from local TV news to amplify the attack. |
Where it ran (delivery by region)
| Ohio | 100.0% |
Who saw it (delivery)
| 45-54 · unknown | 0.1% |
| 35-44 · female | 6.8% |
| 35-44 · unknown | 0.1% |
| 55-64 · unknown | 0.1% |
| 25-34 · unknown | 0.0% |
| 18-24 · female | 0.9% |
| 25-34 · female | 3.9% |
| 45-54 · male | 10.0% |
| 55-64 · male | 12.1% |
| 65+ · unknown | 0.2% |
| 65+ · female | 16.8% |
| 45-54 · female | 7.6% |
| 35-44 · male | 9.4% |
| 55-64 · female | 10.9% |
| 65+ · male | 14.2% |
| 25-34 · male | 5.3% |
| 18-24 · male | 1.5% |
| 18-24 · unknown | 0.0% |
