Abdul El-Sayed US Inactive
Abdul for U.S. Senate
Another poll >>
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Ad copy
This latest poll now makes it clear – our AIPAC-backed opponent is gaining on us. They’ve been flooding the airwaves with millions of dollars’ worth of ads, and it’s working. We just launched our own TV ad, but keeping it on the air takes resources we can only get from you. Rush a $5 donation right now to help us counter AIPAC’s spending and keep us on the air.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 42.7/100 |
| Spend / Reach / Long. / Eff. | 30.5 · 72.4 · 2.2 · 65.7 |
| Spend range | USD 800–899 |
| Impressions | 60,000 – 69,999 |
| CPM (≈ $/1k impr) | USD 13.07 |
| Est. audience size | — |
| Days live | 9 (2026-06-18 → 2026-06-27) |
| Created | 2026-06-17 |
| 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 | democracy elections |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | money cash |
| Call to action | donate |
| Standout element | Red arrow pointing to Stevens +15 poll number dramatizing the urgency of the opponent's rise |
| Tactic | Classic urgency-and-threat fundraising tactic that weaponizes a poll showing the opponent gaining to trigger small-dollar donations by framing AIPAC spending as the villain threatening an underdog campaign. |
Where it ran (delivery by region)
| Michigan | 49.7% |
| California | 7.4% |
| New York | 5.7% |
| Illinois | 3.8% |
| Texas | 3.0% |
| Florida | 2.2% |
| Ohio | 2.2% |
Who saw it (delivery)
| 18-24 · female | 5.3% |
| 45-54 · unknown | 0.1% |
| Unknown · female | 0.0% |
| 65+ · unknown | 0.1% |
| 65+ · male | 2.2% |
| 65+ · female | 1.8% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 2.3% |
| 55-64 · female | 1.9% |
| 45-54 · male | 4.7% |
| 18-24 · male | 14.6% |
| 45-54 · female | 2.8% |
| 35-44 · unknown | 0.5% |
| 35-44 · male | 14.6% |
| 35-44 · female | 7.3% |
| 25-34 · unknown | 1.0% |
| 25-34 · male | 28.1% |
| 25-34 · female | 12.0% |
| 18-24 · unknown | 0.7% |
| Unknown · male | 0.0% |
