Abdul for U.S. Senate
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The newest poll has me worried. We’re in the lead, but our opponent and her AIPAC dollars are reaching undecided voters, and now she’s surged by 15 points in this latest poll. We can’t lose our momentum now. If we can keep our ads on the air and reach Michiganders who haven’t heard our case yet, we’ll hold on to our lead and win. But if AIPAC dominates the airwaves, we could lose steam. This is a make-or-break moment, and donations from grassroots donors like you are the only thing standing between us and AIPAC buying this seat. So if you can, will you chip in $5 right now so we can hold our lead?
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| Overall score | 46.7/100 |
| Spend / Reach / Long. / Eff. | 41.0 · 80.0 · 1.7 · 64.0 |
| Spend range | USD 2,000–2,499 |
| Impressions | 125,000 – 149,999 |
| CPM (≈ $/1k impr) | USD 16.36 |
| Est. audience size | — |
| Days live | 7 (2026-06-22 → active) |
| Created | 2026-06-22 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MI — Abdul El-Sayed |
| Surfaced by | “senate:Abdul El-Sayed” |
| Issue | democracy elections |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | money cash |
| Call to action | donate |
| Standout element | Red arrow pointing down to opponent's surging poll number, contrasting blue text labeling her as the 'AIPAC Opponent' |
| Tactic | Classic fear-based fundraising urgency tactic: framing a poll surge as a financial threat to mobilize grassroots donors against a named outside antagonist (AIPAC), positioning small donations as the democratic counterweight to corporate/PAC money. |
| Michigan | 44.7% |
| California | 8.0% |
| New York | 7.8% |
| Illinois | 4.2% |
| Texas | 3.4% |
| New Jersey | 2.4% |
| Florida | 2.3% |
| 18-24 · female | 3.0% |
| 45-54 · unknown | 0.2% |
| Unknown · female | 0.0% |
| 65+ · unknown | 0.2% |
| 65+ · male | 4.3% |
| 65+ · female | 4.6% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 4.7% |
| 55-64 · female | 3.7% |
| 45-54 · male | 7.3% |
| 18-24 · male | 8.0% |
| 45-54 · female | 4.9% |
| 35-44 · unknown | 0.5% |
| 35-44 · male | 16.8% |
| 35-44 · female | 8.9% |
| 25-34 · unknown | 0.7% |
| 25-34 · male | 21.2% |
| 25-34 · female | 10.4% |
| 18-24 · unknown | 0.3% |
| Unknown · male | 0.0% |