Jeff Wadlin for US Senate - Arkansas 2026 US Inactive
WADLIN FOR SENATE 2026
Ad copy
Tom Cotton has become exactly what Washington wants: a pawn for donors, special interests, and party bosses. While Arkansas families are fighting higher prices, he’s busy with culture wars and national political theater. Tariffs raise costs and punish farmers. Needless wars and foreign policy chaos disrupt oil, fertilizer, and supply chains. Arkansans get stuck with the bill. But the answer is not simply switching from red back to blue, the party that many voters were frustrated with last time. Arkansas deserves something different: a pragmatic, centrist, independent senator who answers only to Arkansans, not party bosses. Not red. Not blue. Arkansas first.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 28.5/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 45.5 · 1.4 · 67.0 |
| Spend range | <USD 99 |
| Impressions | 4,000 – 4,999 |
| CPM (≈ $/1k impr) | USD 11.0 |
| Est. audience size | — |
| Days live | 6 (2026-05-16 → 2026-05-22) |
| Created | 2026-05-16 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | AR — Jeff Wadlin |
| Surfaced by | “senate:Jeff Wadlin” |
🧠 AI analysis
| Issue | economy taxes |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | opponent |
| Symbols | none |
| Call to action | none |
| Standout element | AI-rendered chess pawn topped with Tom Cotton's sculpted head on a dark chessboard, literalizing the 'pawn' metaphor |
| Tactic | The ad weaponizes a single visual pun — 'Pawn Cotton' — using a hyperrealistic AI-generated image of the opponent's face merged with a chess pawn to viscerally communicate the attack that he is controlled by Washington donors and party bosses, making the abstract accusation immediately tangible. |
Where it ran (delivery by region)
| Arkansas | 100.0% |
Who saw it (delivery)
| 18-24 · female | 0.3% |
| 45-54 · male | 6.4% |
| 65+ · male | 28.5% |
| 65+ · female | 30.0% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 12.0% |
| 55-64 · female | 10.1% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 3.9% |
| 18-24 · male | 0.4% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 3.2% |
| 35-44 · female | 1.9% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 1.6% |
| 25-34 · female | 0.9% |
| 65+ · unknown | 0.6% |
