Ben Ray Luján US Inactive
PEOPLE FOR BEN
10,000 SIGNATURES NEEDED >>
STOP Trump from slashing Social Security!
Ad copy
I’m horrified. Donald Trump just confirmed Social Security is on the chopping block. I will NOT allow him to slash our seniors’ hard-earned benefits to fund tax breaks for billionaires. I need 10,000 emergency signatures before midnight. ⬇️
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 48.9/100 |
| Spend / Reach / Long. / Eff. | 34.7 · 59.2 · 48.5 · 53.0 |
| Spend range | USD 1,000–1,499 |
| Impressions | 15,000 – 19,999 |
| CPM (≈ $/1k impr) | USD 71.4 |
| Est. audience size | — |
| Days live | 177 (2020-02-05 → 2020-07-31) |
| Created | 2020-02-05 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | NM — Ben Ray Luján |
| Surfaced by | “senate:NM — Ben Ray Luján” |
🧠 AI analysis
| Issue | social security medicare |
| Framing | attack opponent |
| Message type | list building survey |
| Emotional appeal | urgency |
| Production tier | unknown |
| Who pictured | none |
| Symbols | none |
| Call to action | sign petition |
| Standout element | content removed notice replacing the actual ad creative |
| Tactic | The ad copy uses fear and urgency tactics — a midnight deadline and 10,000 signature goal — to mobilize opposition to Trump's alleged Social Security cuts, but the creative was removed by Facebook for disclaimer non-compliance. |
Where it ran (delivery by region)
| California | 12.0% |
| New York | 7.3% |
| Florida | 6.6% |
| Texas | 5.9% |
| Washington | 4.0% |
| Illinois | 4.0% |
| Pennsylvania | 3.6% |
Who saw it (delivery)
| 18-24 · unknown | 0.0% |
| 25-34 · female | 1.1% |
| 65+ · male | 16.9% |
| 35-44 · male | 1.3% |
| 45-54 · male | 2.7% |
| 45-54 · female | 4.6% |
| 18-24 · male | 0.4% |
| 55-64 · female | 19.0% |
| 55-64 · male | 7.8% |
| 55-64 · unknown | 0.2% |
| 65+ · female | 41.8% |
| 25-34 · male | 1.1% |
| 45-54 · unknown | 0.1% |
| 25-34 · unknown | 0.1% |
| 35-44 · unknown | 0.0% |
| 65+ · unknown | 0.6% |
| 35-44 · female | 1.7% |
| 18-24 · female | 0.5% |
