James Talarico US Inactive
TALARICO FOR TEXAS
Donate to James Talarico for the U.S. Senate
James is running for Senate to take on billionaires and their puppet politicians.
Ad copy
Meet Ken Paxton: He was impeached by his own party in Texas and narrowly spared conviction after his billionaire donors gave $3 million to the impeachment judge. Now, he is running against James Talarico to represent Texas in the U.S. Senate. James believes this kind of corruption is the rot at the core of this broken system and is running an honest campaign to represent all Texans. So if you knew chipping in $20.26 would ensure Ken Paxton never made it to the U.S. Senate, wouldn’t you make the donation?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 57.5/100 |
| Spend / Reach / Long. / Eff. | 72.5 · 100.0 · 0.6 · 56.9 |
| Spend range | USD 40,000–44,999 |
| Impressions | 1,000,000 – 0 |
| CPM (≈ $/1k impr) | USD 42.5 |
| Est. audience size | — |
| Days live | 3 (2026-05-27 → 2026-05-30) |
| Created | 2026-05-27 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | TX — James Talarico |
| Surfaced by | “senate:James Talarico” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | attack opponent |
| Message type | fundraising |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | opponent |
| Symbols | none |
| Call to action | donate |
| Standout element | Ken Paxton's actual booking mugshot paired with his official arrest record and fraud charges |
| Tactic | The ad weaponizes Paxton's real criminal booking record as visual evidence of corruption, using fear and anger to convert outrage into a $20.26 donation with a direct urgency ask. |
Where it ran (delivery by region)
| Texas | 33.9% |
| California | 9.4% |
| Florida | 3.9% |
| New York | 3.9% |
| Washington | 3.1% |
| Illinois | 3.0% |
| Colorado | 2.5% |
Who saw it (delivery)
| 18-24 · female | 0.2% |
| 45-54 · male | 11.2% |
| 65+ · unknown | 0.4% |
| 65+ · male | 13.1% |
| 65+ · female | 14.1% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 11.7% |
| 55-64 · female | 10.7% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 8.9% |
| 18-24 · male | 0.7% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 11.6% |
| 35-44 · female | 7.6% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 5.8% |
| 25-34 · female | 3.0% |
| 18-24 · unknown | 0.0% |
| Unknown · female | 0.0% |
