Dakarai Larriett for Senate US Inactive
ELECT DAKARAI LARRIETT
Ad copy
When you elect someone to represent you, the hope is that you can trust them to uphold the qualities and attributes of a true leader: trustworthiness, integrity, understanding, and compassion. When a person demonstrates to their own family they don’t have those qualities, it gives you pause. To be endorsed by Kelvin and Maurice Wess, who happen to be the brothers of my opponent Everett Wess, was certainly unexpected— but welcome nonetheless! Trustworthiness and integrity are important life, and absolutely should be important for our next Alabama Senator. Will we see you at the polls on June 16th? #DakaraiLarriett #ALSenateRace #Alabama #ALPolitics
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 45.0/100 |
| Spend / Reach / Long. / Eff. | 29.2 · 78.0 · 1.9 · 70.7 |
| Spend range | USD 700–799 |
| Impressions | 100,000 – 124,999 |
| CPM (≈ $/1k impr) | USD 6.66 |
| Est. audience size | — |
| Days live | 8 (2026-06-09 → 2026-06-17) |
| Created | 2026-06-08 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | — |
| Candidate | AL — Dakarai Larriett |
| Surfaced by | “senate:Dakarai Larriett” |
🧠 AI analysis
| Issue | candidate character bio |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | urgency |
| Production tier | diy amateur |
| Who pictured | none |
| Symbols | none |
| Call to action | vote |
| Standout element | Opponent's own family member on camera undercutting him — a rare and damaging endorsement contrast |
| Tactic | The ad weaponizes family betrayal as a character attack, using the opponent's own brothers as endorsers to cast doubt on his integrity without the candidate directly going negative. |
Where it ran (delivery by region)
| Alabama | 100.0% |
Who saw it (delivery)
| 18-24 · female | 1.1% |
| 45-54 · unknown | 0.1% |
| Unknown · female | 0.0% |
| 65+ · unknown | 0.1% |
| 65+ · male | 8.8% |
| 65+ · female | 7.0% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 12.6% |
| 55-64 · female | 6.3% |
| 45-54 · male | 14.3% |
| 18-24 · male | 11.2% |
| 45-54 · female | 4.3% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 13.2% |
| 35-44 · female | 3.2% |
| 25-34 · unknown | 0.2% |
| 25-34 · male | 15.6% |
| 25-34 · female | 1.6% |
| 18-24 · unknown | 0.3% |
| Unknown · male | 0.0% |
