Melisa Franzen for Senate
We can take the Minnesota Senate majority, elect Joe Biden and Kamala Harris, and re-elect Senator Tina Smith and Congressman Dean Phillips — but I need your help to turn out voters across Minnesota. Can you chip in $10 before Friday?
⏰ We are just days away from the most crucial election of our time, and there is so much at stake. We can take the Minnesota Senate majority, elect Joe Biden and Kamala Harris, and re-elect Senator Tina Smith and Congressman Dean Phillips — but I need your help to turn out voters across Minnesota. Can you chip in $10 before Friday?
↗ View in Meta Ad Library (the live creative — image/video/layout)
| Overall score | 31.9/100 |
| Spend / Reach / Long. / Eff. | 17.4 · 50.6 · 1.1 · 58.7 |
| Spend range | USD 200–299 |
| Impressions | 7,000 – 7,999 |
| CPM (≈ $/1k impr) | USD 33.27 |
| Est. audience size | 1,001 – 5,000 |
| Days live | 5 (2020-10-22 → 2020-10-27) |
| Created | 2020-10-22 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MN — Melisa Lopez Franzen |
| Surfaced by | “senate:Melisa Lopez Franzen” |
| Issue | democracy elections |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | diy amateur |
| Who pictured | none |
| Symbols | none |
| Call to action | donate |
| Standout element | Facebook content removal notice replacing the actual ad creative, citing policy non-compliance on disclaimer |
| Tactic | A deadline-driven urgency fundraising ask tied to the presidential ticket coattail effect, rendered moot by the ad's removal for missing a required political disclaimer. |
| Minnesota | 93.6% |
| California | 0.8% |
| Arizona | 0.6% |
| Florida | 0.5% |
| Massachusetts | 0.4% |
| Wisconsin | 0.4% |
| New York | 0.3% |
| 25-34 · unknown | 0.1% |
| 65+ · male | 10.2% |
| 35-44 · unknown | 0.3% |
| 55-64 · unknown | 0.5% |
| 65+ · unknown | 0.5% |
| 18-24 · female | 1.2% |
| 18-24 · male | 1.1% |
| 65+ · female | 22.0% |
| 25-34 · female | 4.5% |
| 18-24 · unknown | 0.2% |
| 55-64 · male | 6.8% |
| 45-54 · female | 13.0% |
| 25-34 · male | 3.0% |
| 35-44 · male | 5.7% |
| 45-54 · male | 6.5% |
| 35-44 · female | 9.4% |
| 55-64 · female | 14.9% |
| 45-54 · unknown | 0.1% |