Abdul El-Sayed US ● Active
Abdul for U.S. Senate
Rush a donation
Ad copy
Look, I’m going to be honest. If we’re going to pull off this win, we need to see a big jump in fundraising right now. We can’t afford to slow down. We may be leading in the polls, but millions upon millions of dollars are flooding in from AIPAC and corporate PACs to prop up my opponents. I don’t take corporate money. I rely solely on people like you to back this movement. Help us cross the finish line strong. Rush a donation today. >>
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 44.1/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 73.9 · 2.8 · 61.3 |
| Spend range | USD 1,500–1,999 |
| Impressions | 70,000 – 79,999 |
| CPM (≈ $/1k impr) | USD 23.33 |
| Est. audience size | — |
| Days live | 11 (2026-06-18 → active) |
| 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 | healthcare |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | healthcare, money cash |
| Call to action | donate |
| Standout element | candidate grinning playfully while smelling colorful peonies against a Medicare for All banner — disarming warmth amid an urgent fundraising ask |
| Tactic | The whimsical, approachable flower-sniffing image creates parasocial warmth and trust, making the hard fundraising pitch feel like a candid honest conversation rather than a transactional appeal. |
Where it ran (delivery by region)
| Michigan | 53.1% |
| California | 6.7% |
| New York | 5.9% |
| Illinois | 3.5% |
| Texas | 3.0% |
| New Jersey | 2.0% |
| Ohio | 2.0% |
Who saw it (delivery)
| 18-24 · female | 2.4% |
| 45-54 · unknown | 0.3% |
| Unknown · female | 0.0% |
| 65+ · unknown | 0.2% |
| 65+ · male | 3.9% |
| 65+ · female | 8.0% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 4.3% |
| 55-64 · female | 7.1% |
| 45-54 · male | 6.4% |
| 18-24 · male | 5.4% |
| 45-54 · female | 7.9% |
| 35-44 · unknown | 0.5% |
| 35-44 · male | 13.5% |
| 35-44 · female | 11.8% |
| 25-34 · unknown | 0.6% |
| 25-34 · male | 16.5% |
| 25-34 · female | 10.8% |
| 18-24 · unknown | 0.3% |
| Unknown · male | 0.0% |
