Abdul El-Sayed US Inactive
Abdul for U.S. Senate
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Ad copy
One of our opponents is out here campaigning with AIPAC. I’m focused on what matters most to the people of Michigan. We need to be prepared for AIPAC to spend big against us to try to tip this primary toward their preferred candidate. Can you pitch in $5 right now so we have the resources to fight back?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 41.4/100 |
| Spend / Reach / Long. / Eff. | 34.7 · 68.1 · 3.3 · 59.6 |
| Spend range | USD 1,000–1,499 |
| Impressions | 40,000 – 44,999 |
| CPM (≈ $/1k impr) | USD 29.4 |
| Est. audience size | — |
| Days live | 13 (2026-03-17 → 2026-03-30) |
| Created | 2026-03-17 |
| Creative variants | 1 body · 1 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 | fundraising |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | opponent, candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Nested tweet screenshot showing AIPAC thanking opponent Rep. Haley Stevens, used as opposition evidence |
| Tactic | The ad weaponizes a real AIPAC tweet endorsing the opponent to fundraise off anti-AIPAC sentiment, framing the race as a grassroots-vs-outside-money contrast to drive small-dollar donations. |
Where it ran (delivery by region)
| Michigan | 41.5% |
| New York | 8.1% |
| Illinois | 6.7% |
| California | 6.4% |
| Ohio | 3.0% |
| New Jersey | 3.0% |
| Massachusetts | 2.9% |
Who saw it (delivery)
| 18-24 · female | 0.4% |
| 45-54 · male | 10.8% |
| 65+ · unknown | 0.3% |
| 65+ · male | 8.6% |
| 65+ · female | 8.6% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 7.6% |
| 55-64 · female | 6.4% |
| 45-54 · unknown | 0.3% |
| 45-54 · female | 7.2% |
| 18-24 · male | 1.3% |
| 35-44 · unknown | 0.8% |
| 35-44 · male | 18.3% |
| 35-44 · female | 9.5% |
| 25-34 · unknown | 0.5% |
| 25-34 · male | 13.8% |
| 25-34 · female | 5.2% |
| 18-24 · unknown | 0.1% |
| Unknown · male | 0.0% |
