Veronica Fernandez for US Senate US Inactive
VERONICA FERNANDEZ FOR US SENATE
⚠ Creative removed by Meta
This ad's image was taken down for violating Meta's ad standards; the copy below is preserved from the Ad Library.
This ad's image was taken down for violating Meta's ad standards; the copy below is preserved from the Ad Library.
Ad copy
Non partisan, bi-partisan and study after study PROVE Medicare for All is the best and least expensive way to provide healthcare to all Americans. We don't have it because the healthcare industry provide Congress AND media with billions in donations and revenue. DO YOUR OWN RESEARCH! Check how much YOU pay for inflated healthcare premiums in your local budget. That would END with M4A and NJ Property taxes will go down!
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 29.4/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 47.5 · 1.7 · 68.5 |
| Spend range | <USD 99 |
| Impressions | 5,000 – 5,999 |
| CPM (≈ $/1k impr) | USD 9.0 |
| Est. audience size | — |
| Days live | 7 (2020-08-24 → 2020-08-31) |
| Created | 2020-08-24 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | NJ — Veronica Fernandez |
| Surfaced by | “senate:Veronica Fernandez” |
🧠 AI analysis
| Issue | healthcare |
| Framing | issue advocacy |
| Message type | persuasion |
| Emotional appeal | anger |
| Production tier | diy amateur |
| Who pictured | candidate |
| Symbols | healthcare, money cash |
| Call to action | none |
| Standout element | Facebook content removal notice replacing the actual ad, exposing platform censorship as part of the message |
| Tactic | The ad leverages populist outrage by framing Medicare for All as suppressed truth, accusing the healthcare industry and media of corruption, and tying M4A directly to NJ property tax relief to make the issue locally tangible. |
Where it ran (delivery by region)
| New Jersey | 100.0% |
Who saw it (delivery)
| 18-24 · unknown | 0.1% |
| 65+ · female | 15.1% |
| 18-24 · female | 1.0% |
| 45-54 · female | 4.4% |
| 25-34 · female | 1.7% |
| 35-44 · female | 1.3% |
| 45-54 · male | 12.0% |
| 35-44 · male | 7.3% |
| 55-64 · male | 17.2% |
| 35-44 · unknown | 0.1% |
| 25-34 · male | 6.9% |
| 55-64 · female | 9.4% |
| 18-24 · male | 3.7% |
| 65+ · male | 18.7% |
| 55-64 · unknown | 0.3% |
| 45-54 · unknown | 0.2% |
| 65+ · unknown | 0.2% |
| 25-34 · unknown | 0.2% |
