Chris Coons US Inactive
Chris Coons for Delaware
Sign the petition now
Protect American workers
Ad copy
Unions helped create America’s middle class, but Donald Trump and his Republican allies continue to attack a worker's right to organize. Chris Coons is working with Democrats in Congress to protect the right to organize — but your voice needs to be heard. Sign the petition now >> https://bit.ly/2WsCayc
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 49.2/100 |
| Spend / Reach / Long. / Eff. | 46.5 · 78.0 · 13.5 · 58.7 |
| Spend range | USD 3,500–3,999 |
| Impressions | 100,000 – 124,999 |
| CPM (≈ $/1k impr) | USD 33.33 |
| Est. audience size | — |
| Days live | 50 (2019-06-11 → 2019-07-31) |
| Created | 2019-06-11 |
| Creative variants | 1 body · 1 headline |
| Platforms | — |
| Languages | en |
| Candidate | DE — Chris Coons |
| Surfaced by | “senate:Chris Coons” |
🧠 AI analysis
| Issue | jobs labor |
| Framing | contrast comparison |
| Message type | list building survey |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | workers labor, opponent |
| Symbols | factory industry |
| Call to action | sign petition |
| Standout element | Split image juxtaposing a hard-hat factory worker above with unflattering close-ups of Trump and McConnell below, separated by bold red headline text |
| Tactic | The ad uses a classic contrast frame — heroic worker vs. villainous opponents — to drive petition signatures while building Coons' list by channeling anger at Trump and McConnell into grassroots action. |
Where it ran (delivery by region)
| California | 11.5% |
| Florida | 7.7% |
| Texas | 6.2% |
| New York | 5.9% |
| Illinois | 4.4% |
| Michigan | 4.3% |
| Pennsylvania | 4.2% |
Who saw it (delivery)
| 65+ · male | 21.4% |
| 55-64 · unknown | 0.2% |
| 35-44 · unknown | 0.0% |
| 45-54 · unknown | 0.1% |
| 65+ · unknown | 0.5% |
| 25-34 · female | 0.6% |
| 25-34 · male | 0.8% |
| 18-24 · female | 0.3% |
| 35-44 · female | 1.0% |
| 65+ · female | 42.5% |
| 18-24 · male | 0.2% |
| 45-54 · female | 3.4% |
| 35-44 · male | 1.3% |
| 45-54 · male | 3.4% |
| 55-64 · male | 10.3% |
| 55-64 · female | 14.1% |
| 25-34 · unknown | 0.0% |
