ANGIE CRAIG FOR MINNESOTA
Must-win race
I’m the Democrat running to HOLD Minnesota's crucial U.S. Senate seat – will you let me introduce myself? I was raised by a single mom and grew up in a mobile home park. I watched my mom work hard while raising three kids. I worked my way through college, started a career as a newspaper reporter and eventually led a workforce for a major Minnesota manufacturer. I worked hard to get where I am, but I was pretty lucky, too. Now, Donald Trump is making it harder for families like the one I grew up in to get ahead. That’s why I’m running for Senate to stop Trump and win a bright future for my state. My campaign has set a goal to raise $500,000 around our launch. Please, will you join me in this fight by rushing a donation and get us closer to flipping the U.S. Senate blue?
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| Overall score | 48.3/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 66.9 · 32.0 · 56.2 |
| Spend range | USD 1,500–1,999 |
| Impressions | 35,000 – 39,999 |
| CPM (≈ $/1k impr) | USD 46.65 |
| Est. audience size | — |
| Days live | 117 (2025-05-09 → 2025-09-03) |
| Created | 2025-05-09 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MN — Angie Craig |
| Surfaced by | “senate:Angie Craig” |
| Issue | candidate character bio |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | empathy |
| Production tier | professional |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Candidate in approachable blue blazer speaking directly to camera with a warm, relatable personal backstory framing |
| Tactic | Uses a classic origin-story fundraising tactic — pairing a humble upbringing narrative with a midnight deadline urgency cue to drive small-dollar ActBlue donations from emotionally engaged supporters. |
| California | 13.2% |
| Minnesota | 7.1% |
| New York | 5.3% |
| Texas | 5.0% |
| Florida | 4.6% |
| Washington | 4.3% |
| Illinois | 4.1% |
| 18-24 · female | 0.4% |
| 45-54 · male | 3.3% |
| 65+ · male | 33.2% |
| 65+ · female | 32.2% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 9.7% |
| 55-64 · female | 9.6% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 2.9% |
| 18-24 · male | 0.6% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 1.9% |
| 35-44 · female | 1.8% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 1.9% |
| 25-34 · female | 1.4% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.6% |