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/2MDYXYb
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 41.0/100 |
| Spend / Reach / Long. / Eff. | 31.7 · 61.7 · 13.5 · 56.9 |
| Spend range | USD 900–999 |
| Impressions | 20,000 – 24,999 |
| CPM (≈ $/1k impr) | USD 42.2 |
| 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, money cash |
| Call to action | sign petition |
| Standout element | Large upward arrow between unflattering close-up photos of Trump and McConnell juxtaposed against a blue-collar factory worker above |
| Tactic | The ad uses a classic contrast split — heroic worker image above, menacing opponent faces below — to emotionally prime anger and channel it into a petition sign-up for list-building purposes. |
Where it ran (delivery by region)
| California | 10.3% |
| Florida | 7.5% |
| New York | 6.8% |
| Texas | 4.6% |
| Pennsylvania | 4.6% |
| Michigan | 4.3% |
| Washington | 4.2% |
Who saw it (delivery)
| 35-44 · unknown | 0.0% |
| 55-64 · unknown | 0.2% |
| 65+ · unknown | 0.6% |
| 35-44 · male | 0.6% |
| 45-54 · female | 1.9% |
| 25-34 · male | 0.3% |
| 45-54 · male | 2.0% |
| 55-64 · male | 8.6% |
| 55-64 · female | 10.3% |
| 45-54 · unknown | 0.0% |
| 35-44 · female | 0.6% |
| 65+ · male | 26.4% |
| 65+ · female | 47.8% |
| 25-34 · unknown | 0.0% |
| 18-24 · male | 0.1% |
| 18-24 · female | 0.2% |
| 25-34 · female | 0.4% |
