Abdul El-Sayed US Inactive
Abdul for U.S. Senate
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Ad copy
A brand-new poll shows that when voters hear what Abdul’s fighting for — Medicare for All, ending corporate greed and stopping Trump’s MAGA agenda — we win. We’re only months away from the primary, and we need to be sure we can reach as many voters as possible before the election. This campaign is fully funded by people like you — not corporate PACs. That’s why I’m counting on your support to keep building this momentum. So if you’re able, can you pitch in $5, $10 — whatever you can — so we reach even more voters across Michigan?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 50.7/100 |
| Spend / Reach / Long. / Eff. | 49.0 · 85.0 · 6.6 · 62.1 |
| Spend range | USD 4,500–4,999 |
| Impressions | 200,000 – 249,999 |
| CPM (≈ $/1k impr) | USD 21.11 |
| Est. audience size | — |
| Days live | 25 (2026-04-01 → 2026-04-26) |
| Created | 2026-04-01 |
| 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 | healthcare |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate, opponent |
| Symbols | none |
| Call to action | donate |
| Standout element | Side-by-side favorability poll bar chart showing El-Sayed leading at 45% over primary rivals with candidate headshots |
| Tactic | The ad weaponizes poll momentum as social proof to trigger urgency-driven small-dollar donations, linking ideological platform to electability before the primary. |
Where it ran (delivery by region)
| Michigan | 31.6% |
| California | 10.8% |
| New York | 7.7% |
| Texas | 5.2% |
| Illinois | 4.5% |
| Florida | 3.8% |
| New Jersey | 2.8% |
Who saw it (delivery)
| 18-24 · female | 1.3% |
| 45-54 · unknown | 0.3% |
| Unknown · female | 0.0% |
| 65+ · unknown | 0.3% |
| 65+ · male | 8.4% |
| 65+ · female | 6.9% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 8.3% |
| 55-64 · female | 5.7% |
| 45-54 · male | 10.8% |
| 18-24 · male | 3.9% |
| 45-54 · female | 6.0% |
| 35-44 · unknown | 0.5% |
| 35-44 · male | 17.3% |
| 35-44 · female | 7.8% |
| 25-34 · unknown | 0.5% |
| 25-34 · male | 15.3% |
| 25-34 · female | 6.1% |
| 18-24 · unknown | 0.2% |
| Unknown · male | 0.0% |
