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Dr. Annie Andrews US Inactive

DR. ANNIE ANDREWS FOR SENATE

ad creative

LINDSEY GRAHAM MUST GO >>

CHIP IN

Ad copy

Lindsey Graham ripped healthcare away from 1 in 5 children because it's a... money laundering scheme??? My name is Dr. Annie Andrews and as a mom and pediatrician, I know that the children who were relying on Medicaid were NOT laundering money. Let’s be real: Lindsey Graham gutted Medicaid to make his billionaire donors even richer. Help me kick Lindsey Graham out of office and flip the Senate by rushing a donation to my campaign right now >>

↗ View in Meta Ad Library (the live creative — image/video/layout)

Performance proxies

Overall score57.0/100
Spend / Reach / Long. / Eff.63.0 · 78.0 · 39.7 · 47.2
Spend rangeUSD 15,000–19,999
Impressions100,000 – 124,999
CPM (≈ $/1k impr)USD 155.55
Est. audience size50,001 – 100,000
Days live145 (2025-07-18 → 2025-12-10)
Created2025-07-17
Creative variants1 body · 1 headline
Platformsfacebook, instagram
Languagesen
CandidateSC — Annie Andrews
Surfaced by“senate:Annie Andrews”

🧠 AI analysis

Issuehealthcare
Framingcontrast comparison
Message typefundraising
Emotional appealanger
Production tierdiy amateur
Who picturedcandidate, medical
Symbolshealthcare, money cash
Call to actiondonate
Standout elementbold yellow-and-white 'NOT LAUNDERING MONEY' subtitle overlaid on a close-up selfie-style video of a pediatrician in scrubs
TacticThe ad weaponizes Graham's own rhetoric by repeating his 'money laundering' framing to absurdity, using a credentialed doctor-mom as a trusted messenger to make the Medicaid cuts feel personally outrageous and drive immediate donations.

Where it ran (delivery by region)

South Carolina15.0%
California12.5%
Florida5.5%
New York5.5%
Texas3.9%
North Carolina3.9%
Washington3.7%

Who saw it (delivery)

18-24 · female 0.1%
45-54 · male 2.2%
65+ · unknown 0.9%
65+ · male 26.8%
65+ · female 41.2%
55-64 · unknown 0.2%
55-64 · male 6.4%
55-64 · female 12.2%
45-54 · unknown 0.1%
45-54 · female 4.6%
18-24 · male 0.1%
35-44 · unknown 0.1%
35-44 · male 1.1%
35-44 · female 2.5%
25-34 · unknown 0.0%
25-34 · male 0.5%
25-34 · female 0.9%
18-24 · unknown 0.0%
Unknown · male 0.0%

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