Abdul El-Sayed US ● Active
Abdul for U.S. Senate
Final EOQ Deadline Approaching
Ad copy
Our final FEC deadline before the primary election is June 30. The fundraising numbers we’ll report after that deadline will be the last public snapshot of where this race stands before voters head to the polls – and I’d be lying if I said it didn’t matter. AIPAC-linked groups are spending millions on ads to stop us, and we can’t slow down for even a second. I know we can win this race. We’re leading in the polls, running on a popular agenda, and building a broad coalition of support across Michigan – but letting millions of dollars in ads go unanswered could easily bury us. Can you chip in $5 before June 30th to help us close out this quarter strong?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 41.8/100 |
| Spend / Reach / Long. / Eff. | 30.5 · 70.7 · 1.7 · 64.4 |
| Spend range | USD 800–899 |
| Impressions | 50,000 – 59,999 |
| CPM (≈ $/1k impr) | USD 15.45 |
| Est. audience size | — |
| Days live | 7 (2026-06-22 → active) |
| Created | 2026-06-21 |
| 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 | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Bold '$1 MILLION GOAL' headline in blue-and-orange overlaid on candidate portrait with Michigan state silhouette |
| Tactic | Creates urgency by invoking an FEC deadline and naming AIPAC as a wealthy adversary, framing the donation as a necessary counter-punch to big-money outside spending. |
Where it ran (delivery by region)
| Michigan | 64.6% |
| California | 5.1% |
| New York | 4.5% |
| Illinois | 3.1% |
| Texas | 2.0% |
| Ohio | 1.5% |
| Florida | 1.4% |
Who saw it (delivery)
| 18-24 · female | 2.8% |
| 45-54 · unknown | 0.2% |
| Unknown · female | 0.0% |
| 65+ · unknown | 0.2% |
| 65+ · male | 4.4% |
| 65+ · female | 6.7% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 4.9% |
| 55-64 · female | 5.8% |
| 45-54 · male | 7.4% |
| 18-24 · male | 6.8% |
| 45-54 · female | 6.7% |
| 35-44 · unknown | 0.5% |
| 35-44 · male | 14.1% |
| 35-44 · female | 10.7% |
| 25-34 · unknown | 0.7% |
| 25-34 · male | 17.6% |
| 25-34 · female | 9.9% |
| 18-24 · unknown | 0.3% |
| Unknown · male | 0.0% |
