Peggy Flanagan for Minnesota
Stand with Peggy
Stand with Peggy
Stand with Peggy
Stand with Peggy
This campaign is powered by grandmas, teachers, and truck drivers – not corporate PACs or billionaires. Can you chip in today?
This campaign is powered by grandmas, teachers, and truck drivers – not corporate PACs or billionaires. Can you chip in today?
This campaign is powered by grandmas, teachers, and truck drivers – not corporate PACs or billionaires. Can you chip in today?
This campaign is powered by grandmas, teachers, and truck drivers – not corporate PACs or billionaires. Can you chip in today?
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| Overall score | 52.4/100 |
| Spend / Reach / Long. / Eff. | 50.6 · 80.0 · 21.8 · 57.3 |
| Spend range | USD 5,000–5,999 |
| Impressions | 125,000 – 149,999 |
| CPM (≈ $/1k impr) | USD 40.0 |
| Est. audience size | — |
| Days live | 80 (2025-07-28 → 2025-10-16) |
| Created | 2025-07-28 |
| Creative variants | 4 body · 4 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MN — Peggy Flanagan |
| Surfaced by | “senate:Peggy Flanagan” |
| Issue | economy taxes |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | empathy |
| Production tier | diy amateur |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | low-fi selfie-style video frame evoking authenticity and grassroots intimacy |
| Tactic | The populist contrast of 'grandmas, teachers, and truck drivers' versus 'corporate PACs or billionaires' deploys a classic us-vs-them fundraising appeal designed to motivate small-dollar donors through class solidarity and anti-elite sentiment. |
| Minnesota | 80.1% |
| California | 2.4% |
| Wisconsin | 1.9% |
| New York | 1.0% |
| Washington | 0.9% |
| North Dakota | 0.8% |
| Illinois | 0.8% |
| 18-24 · female | 1.2% |
| 45-54 · male | 5.4% |
| 65+ · male | 12.3% |
| 65+ · female | 20.6% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 6.6% |
| 55-64 · female | 13.3% |
| 45-54 · unknown | 0.3% |
| 45-54 · female | 12.0% |
| 18-24 · male | 0.9% |
| 35-44 · unknown | 0.4% |
| 35-44 · male | 4.9% |
| 35-44 · female | 11.5% |
| 25-34 · unknown | 0.3% |
| 25-34 · male | 3.1% |
| 25-34 · female | 6.3% |
| 18-24 · unknown | 0.1% |
| 65+ · unknown | 0.5% |