Abdul El-Sayed US ● Active
Abdul for U.S. Senate
Ad copy
⏱️ During this ad, Trump spent $161,000 of your tax dollars on his war with Iran. That's a billion dollars a day that should be in your pocket, building better schools, roads, factories, and healthcare here in Michigan. Abdul El-Sayed will stop investing in an illegal war and bring that money home. Vote for Abdul El-Sayed by August 4.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 46.8/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 80.0 · 2.8 · 65.9 |
| Spend range | USD 1,500–1,999 |
| Impressions | 125,000 – 149,999 |
| CPM (≈ $/1k impr) | USD 12.72 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 11 (2026-06-18 → active) |
| Created | 2026-06-17 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MI — Abdul El-Sayed |
| Surfaced by | “senate:Abdul El-Sayed” |
🧠 AI analysis
| Issue | foreign policy defense |
| Framing | contrast comparison |
| Message type | persuasion |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | us flag, money cash |
| Call to action | vote |
| Standout element | Live-spending countdown timer gimmick implying real-time waste of taxpayer money during the ad itself |
| Tactic | The real-time dollar counter creates visceral urgency by making the viewer feel personally robbed during the seconds they spend watching, then pivots to domestic investment as the patriotic alternative. |
Where it ran (delivery by region)
| Michigan | 100.0% |
Who saw it (delivery)
| 18-24 · female | 2.5% |
| 45-54 · male | 9.4% |
| 65+ · unknown | 0.2% |
| 65+ · male | 9.8% |
| 65+ · female | 8.6% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 9.1% |
| 55-64 · female | 11.4% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 14.7% |
| 18-24 · male | 1.6% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 7.2% |
| 35-44 · female | 11.6% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 5.3% |
| 25-34 · female | 8.0% |
| 18-24 · unknown | 0.1% |
| Unknown · female | 0.0% |
