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Abdul El-Sayed US Inactive

Abdul for U.S. Senate

ad creative

Fuel Republican Fear | Donate to Abdul

Become a founding donor of our campaign today!

Ad copy

🚨Big news: the Republicans are SCARED of this campaign. The NRSC just attacked me by comparing me to Zohran Mamdani and calling us “anti-American.” Why? Because we’re both proud Muslim Americans who aren’t afraid to fight for what people deserve. I believe healthcare is a human right. That corporations shouldn’t buy our democracy. And that no one should go broke trying to live a decent life. If that’s considered “anti-American,” maybe the NRSC needs to rethink what this country stands for. They’re right to be worried — because we’re building a people-powered movement that can win in Michigan. If you’re with me, will you chip in $10 to my campaign today to build our grassroots momentum? We can’t do it without you. Thank you.

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Performance proxies

Overall score42.9/100
Spend / Reach / Long. / Eff.30.5 · 72.4 · 3.0 · 65.7
Spend rangeUSD 800–899
Impressions60,000 – 69,999
CPM (≈ $/1k impr)USD 13.07
Est. audience size
Days live12 (2025-06-26 → 2025-07-08)
Created2025-06-26
Creative variants1 body · 1 headline
Platformsfacebook, instagram
Languagesen
CandidateMI — Abdul El-Sayed
Surfaced by“senate:Abdul El-Sayed”

🧠 AI analysis

Issuehealthcare
Framingcontrast comparison
Message typefundraising
Emotional appealfear
Production tiersemi pro
Who picturednone
Symbolsnone
Call to actiondonate
Standout elementScreenshot of NRSC tweet used as proof of Republican fear and anti-Muslim bias
TacticJudo-flip tactic turns an opponent attack into a fundraising rallying cry by framing Republican criticism as validation of the campaign's threat and Muslim American identity as a badge of pride.

Where it ran (delivery by region)

New York14.8%
California14.4%
Michigan9.8%
Texas8.8%
New Jersey6.2%
Illinois6.1%
Florida4.2%

Who saw it (delivery)

18-24 · female 1.2%
45-54 · male 9.7%
65+ · male 2.7%
65+ · female 2.5%
55-64 · unknown 0.2%
55-64 · male 3.7%
55-64 · female 2.9%
45-54 · unknown 0.3%
45-54 · female 6.0%
18-24 · male 3.4%
35-44 · unknown 0.5%
35-44 · male 23.9%
35-44 · female 13.7%
25-34 · unknown 0.4%
25-34 · male 19.5%
25-34 · female 9.1%
18-24 · unknown 0.2%
65+ · unknown 0.1%

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