Angie Craig US Inactive
ANGIE CRAIG FOR MINNESOTA
Help Angie fight Trump & Musk
Flip the Senate blue
Ad copy
BREAKING NEWS: Democratic Congresswoman Angie Craig launches campaign for U.S. Senate to stop Elon Musk Elon Musk is using his power to try to gut Social Security and Medicare, raise costs on working Americans and destroy our government. ENOUGH! Angie has what it takes to fight Elon Musk and his DOGE boys – but her campaign needs your personal endorsement to get out of the gate strong. Will you add your name now to endorse Angie's campaign to stop Elon Musk?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 45.6/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 70.7 · 14.6 · 59.0 |
| Spend range | USD 1,500–1,999 |
| Impressions | 50,000 – 59,999 |
| CPM (≈ $/1k impr) | USD 31.81 |
| Est. audience size | — |
| Days live | 54 (2025-05-09 → 2025-07-02) |
| Created | 2025-05-08 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MN — Angie Craig |
| Surfaced by | “senate:Angie Craig” |
🧠 AI analysis
| Issue | social security medicare |
| Framing | contrast comparison |
| Message type | list building survey |
| Emotional appeal | anger |
| Production tier | professional |
| Who pictured | candidate |
| Symbols | none |
| Call to action | sign petition |
| Standout element | Bold red 'ENDORSE' CTA button overlaid on candidate photo mirrors a news-breaking urgency frame |
| Tactic | Frames Elon Musk as the villain threatening Social Security and Medicare to drive list-building endorsement sign-ups, using 'BREAKING NEWS' urgency language and the DOGE controversy as a fundraising hook. |
Where it ran (delivery by region)
| California | 6.1% |
| Florida | 6.1% |
| Ohio | 5.6% |
| Michigan | 5.3% |
| Pennsylvania | 4.6% |
| Texas | 4.6% |
| New York | 4.6% |
Who saw it (delivery)
| 18-24 · female | 0.2% |
| 45-54 · male | 2.1% |
| 65+ · male | 23.9% |
| 65+ · female | 45.9% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 7.3% |
| 55-64 · female | 11.7% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 3.2% |
| 18-24 · male | 0.2% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 1.3% |
| 35-44 · female | 1.6% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 0.8% |
| 25-34 · female | 1.0% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.4% |
