Chris Coons US Inactive
Chris Coons for Delaware
Drug prices in 2019 are surging, with hikes at 5 times inflation
Despite President Trump's vow to rein in prices, 17% more drugs have bumped prices compared with 2018
Ad copy
Too many Delawareans and Americans are paying thousands of dollars for life-saving prescription drugs. No one should have to choose between putting food on the table or paying for medication. This year, I have co-sponsored four key pieces of legislation: Empowering Medicare Seniors to Negotiate Prices Act, SPIKE ACT, RxCAP Act, and C-THRU Act. These bills are all aimed at lowering prescription drug prices while increasing transparency. https://cbsn.ws/2SYjpCw
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 40.8/100 |
| Spend / Reach / Long. / Eff. | 25.8 · 65.4 · 8.3 · 63.7 |
| Spend range | USD 500–599 |
| Impressions | 30,000 – 34,999 |
| CPM (≈ $/1k impr) | USD 16.91 |
| Est. audience size | — |
| Days live | 31 (2019-08-16 → 2019-09-16) |
| Created | 2019-08-16 |
| Creative variants | 1 body · 1 headline |
| Platforms | — |
| Languages | en |
| Candidate | DE — Chris Coons |
| Surfaced by | “senate:Chris Coons” |
🧠 AI analysis
| Issue | healthcare |
| Framing | issue advocacy |
| Message type | awareness |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | seniors |
| Symbols | money cash, healthcare |
| Call to action | learn more |
| Standout element | Colorful prescription pills piled on top of a $100 bill featuring Ben Franklin's eyes staring out |
| Tactic | The ad uses a news screenshot and vivid imagery of pills on money to establish urgency and credibility, positioning Coons as a legislative champion against rising drug costs. |
Where it ran (delivery by region)
| Delaware | 11.9% |
| California | 8.5% |
| Florida | 6.4% |
| New York | 5.2% |
| Pennsylvania | 4.7% |
| Texas | 4.2% |
| Michigan | 3.8% |
Who saw it (delivery)
| 25-34 · unknown | 0.0% |
| 65+ · unknown | 0.4% |
| 18-24 · unknown | 0.0% |
| 18-24 · male | 0.2% |
| 18-24 · female | 0.3% |
| 25-34 · female | 0.6% |
| 35-44 · female | 1.3% |
| 55-64 · unknown | 0.2% |
| 35-44 · male | 1.3% |
| 35-44 · unknown | 0.0% |
| 25-34 · male | 0.9% |
| 45-54 · female | 3.5% |
| 45-54 · male | 3.3% |
| 55-64 · male | 9.4% |
| 65+ · male | 20.2% |
| 55-64 · female | 14.0% |
| 65+ · female | 44.2% |
| 45-54 · unknown | 0.1% |
