Abdul for U.S. Senate
‼️ STOP SCROLLING: Did you hear that?? ‼️ I’m Abdul El-Sayed and I’m running for U.S. Senate in Michigan. I’m not taking a cent of corporate PAC money in this race – and let me tell you why. Money is corrupting American politics. It is buying politicians, selling our rights, and leaving us – the American people – poorer, sicker, and angrier. It is distorting reality and rigging the system. Michigan is poised to play an essential role in 2026, which means that corporate PACs will be pouring MILLIONS into my opponent’s race. I’m ready to take them on. Are you? Will you chip in whatever you can to keep our grassroots campaign going?
↗ View in Meta Ad Library (the live creative — image/video/layout)
| Overall score | 45.5/100 |
| Spend / Reach / Long. / Eff. | 23.7 · 59.2 · 38.6 · 60.6 |
| Spend range | USD 400–499 |
| Impressions | 15,000 – 19,999 |
| CPM (≈ $/1k impr) | USD 25.69 |
| Est. audience size | — |
| Days live | 141 (2025-07-10 → 2025-11-28) |
| Created | 2025-07-10 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MI — Abdul El-Sayed |
| Surfaced by | “senate:Abdul El-Sayed” |
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | money cash |
| Call to action | donate |
| Standout element | candidate speaking directly to camera with open hands against dark outdoor background, reinforcing authenticity and anti-establishment sincerity |
| Tactic | The ad weaponizes populist anger against corporate money by having the candidate speak personally and directly, using pattern-interrupt copy ('STOP SCROLLING') to drive emotional investment before hitting a fundraising ask rooted in moral contrast. |
| Michigan | 27.9% |
| California | 9.9% |
| New York | 8.8% |
| Texas | 6.5% |
| Illinois | 6.1% |
| New Jersey | 3.8% |
| Florida | 3.4% |
| 18-24 · female | 0.4% |
| 45-54 · male | 16.0% |
| 65+ · male | 9.3% |
| 65+ · female | 6.3% |
| 55-64 · unknown | 0.4% |
| 55-64 · male | 11.4% |
| 55-64 · female | 5.5% |
| 45-54 · unknown | 0.6% |
| 45-54 · female | 5.5% |
| 18-24 · male | 2.3% |
| 35-44 · unknown | 0.4% |
| 35-44 · male | 20.1% |
| 35-44 · female | 6.3% |
| 25-34 · unknown | 0.2% |
| 25-34 · male | 11.5% |
| 25-34 · female | 3.5% |
| 18-24 · unknown | 0.1% |
| 65+ · unknown | 0.2% |