Chris Coons US Inactive
CHRIS COONS FOR DELAWARE
Add your name now
Protect Social Security and Medicare
Ad copy
President Trump and Senate Republicans have made it crystal clear that they plan to cut Social Security and Medicare. Their first step was to pass massive tax cuts for the wealthy, then use the skyrocketing debt to justify slashing the budgets for Social Security and Medicare. Senator Chris Coons won't stand for it. Add your name to protect Social Security and Medicare from the GOP’s attacks >> https://bit.ly/32clCid
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 50.8/100 |
| Spend / Reach / Long. / Eff. | 44.9 · 80.0 · 17.1 · 61.2 |
| Spend range | USD 3,000–3,499 |
| Impressions | 125,000 – 149,999 |
| CPM (≈ $/1k impr) | USD 23.63 |
| Est. audience size | — |
| Days live | 63 (2020-02-20 → 2020-04-23) |
| Created | 2020-02-19 |
| Creative variants | 1 body · 1 headline |
| Platforms | |
| Languages | en |
| Candidate | DE — Chris Coons |
| Surfaced by | “senate:Chris Coons” |
🧠 AI analysis
| Issue | social security medicare |
| Framing | attack opponent |
| Message type | list building survey |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | opponent |
| Symbols | none |
| Call to action | sign petition |
| Standout element | high-contrast black-and-white close-ups of Trump and McConnell flanking bold yellow warning text |
| Tactic | The ad uses menacing grayscale portraits of Republican opponents paired with urgent yellow text to trigger fear of benefit cuts and drive petition sign-ups. |
Where it ran (delivery by region)
| California | 10.2% |
| New York | 8.2% |
| Florida | 7.6% |
| Texas | 4.9% |
| Pennsylvania | 4.7% |
| Michigan | 4.6% |
| Illinois | 4.4% |
Who saw it (delivery)
| 35-44 · female | 1.8% |
| 25-34 · female | 2.4% |
| 35-44 · unknown | 0.0% |
| 25-34 · unknown | 0.0% |
| 55-64 · unknown | 0.2% |
| 45-54 · unknown | 0.0% |
| 65+ · unknown | 0.4% |
| 18-24 · female | 1.0% |
| 18-24 · male | 0.9% |
| 65+ · female | 37.5% |
| 45-54 · female | 4.2% |
| 35-44 · male | 1.6% |
| 55-64 · female | 13.3% |
| 55-64 · male | 10.4% |
| 65+ · male | 20.9% |
| 25-34 · male | 1.7% |
| 45-54 · male | 3.5% |
| 18-24 · unknown | 0.0% |
