Angie Craig US Inactive
ANGIE CRAIG FOR CONGRESS
angiecraig.com
I’ve prioritized listening to the concerns of the citizens I represent and working across the aisle to create stronger communities and an economy that works for every Minnesotan. That’s why I ran for Congress.
Ad copy
When Angie worked with Savage, MN’s Allie Krueger to close the ACA’s “family glitch,” it didn’t just change the Krueger family’s lives. Five million Americans just like them can afford their care now, too!
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 45.3/100 |
| Spend / Reach / Long. / Eff. | 27.6 · 75.1 · 8.8 · 69.7 |
| Spend range | USD 600–699 |
| Impressions | 80,000 – 89,999 |
| CPM (≈ $/1k impr) | USD 7.64 |
| Est. audience size | 50,001 – 100,000 |
| Days live | 33 (2022-08-31 → 2022-10-03) |
| Created | 2022-08-30 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MN — Angie Craig |
| Surfaced by | “senate:Angie Craig” |
🧠 AI analysis
| Issue | healthcare |
| Framing | positive candidate |
| Message type | persuasion |
| Emotional appeal | hope |
| Production tier | professional |
| Who pictured | candidate, diverse crowd |
| Symbols | healthcare, family |
| Call to action | learn more |
| Standout element | bold underlined 'FIVE MILLION' in high-contrast white text anchoring the policy achievement |
| Tactic | The ad uses a real constituent story to humanize a policy win, pairing a warm candidate photo with a concrete numerical impact claim to build credibility and empathy simultaneously. |
Where it ran (delivery by region)
| Minnesota | 99.2% |
| England | 0.1% |
| Wisconsin | 0.0% |
| Texas | 0.0% |
| Masovian Voivodeship | 0.0% |
| Kuyavian-Pomeranian Voivodeship | 0.0% |
| New Jersey | 0.0% |
Who saw it (delivery)
| 13-17 · unknown | 0.0% |
| 35-44 · female | 12.9% |
| 18-24 · unknown | 0.1% |
| 25-34 · unknown | 0.2% |
| 35-44 · unknown | 0.2% |
| 65+ · unknown | 0.1% |
| 45-54 · male | 7.9% |
| 45-54 · female | 7.7% |
| 35-44 · male | 12.8% |
| 45-54 · unknown | 0.1% |
| 18-24 · female | 6.9% |
| 55-64 · unknown | 0.1% |
| 65+ · female | 4.4% |
| 55-64 · female | 5.6% |
| 25-34 · male | 14.1% |
| 18-24 · male | 5.1% |
| 25-34 · female | 14.2% |
| 55-64 · male | 4.8% |
| 65+ · male | 2.8% |
| 13-17 · female | 0.0% |
| 13-17 · male | 0.0% |
