Dr. Robin Kelly US Inactive
ROBIN KELLY FOR SENATE
I'm Impeaching Kristi Noem
Show your support with a contribution.
Ad copy
I'm impeaching Kristi Noem. One of her rogue ICE agents shot and killed an innocent woman in Minneapolis. Renee Nicole Good is dead because of Noem's reign of terror. She wreaked havoc in Chicago. Now Minneapolis. She's violating the Constitution, ending lives, and separating families. I told my constituents I would fight back. This is me fighting back. But I need your help to win this Senate race so I can keep holding Trump's administration accountable. Chip in $10 today.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 45.4/100 |
| Spend / Reach / Long. / Eff. | 43.1 · 73.9 · 6.6 · 58.0 |
| Spend range | USD 2,500–2,999 |
| Impressions | 70,000 – 79,999 |
| CPM (≈ $/1k impr) | USD 36.66 |
| Est. audience size | — |
| Days live | 25 (2026-01-08 → 2026-02-02) |
| Created | 2026-01-08 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | IL — Robin Kelly |
| Surfaced by | “senate:Robin Kelly” |
🧠 AI analysis
| Issue | immigration |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | candidate, opponent |
| Symbols | none |
| Call to action | donate |
| Standout element | Split-panel contrast showing desaturated Noem on red background vs. smiling Kelly on teal background |
| Tactic | The ad weaponizes a specific named victim — Renee Nicole Good — to make abstract immigration enforcement viscerally personal, then funnels that outrage directly into a $10 donation ask. |
Where it ran (delivery by region)
| California | 11.0% |
| Minnesota | 10.0% |
| New York | 5.9% |
| Florida | 5.3% |
| Texas | 5.0% |
| Illinois | 4.2% |
| Michigan | 4.1% |
Who saw it (delivery)
| 18-24 · female | 1.0% |
| 45-54 · male | 3.5% |
| 65+ · unknown | 0.5% |
| 65+ · male | 15.0% |
| 65+ · female | 25.3% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 5.1% |
| 55-64 · female | 9.7% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 8.0% |
| 18-24 · male | 0.5% |
| 35-44 · unknown | 0.3% |
| 35-44 · male | 4.6% |
| 35-44 · female | 12.1% |
| 25-34 · unknown | 0.2% |
| 25-34 · male | 3.6% |
| 25-34 · female | 10.2% |
| 18-24 · unknown | 0.0% |
| Unknown · unknown | 0.0% |
