Dr. Lorita Daniels for US Senate US Inactive
LORITA DANIELS FOR US SENATE
Ad copy
I’ll be honest, I don’t think this is a tough choice. I’m not running to protect corporate developers. I’m running to make sure working families can afford to live in the communities they help build. So I want to hear from you. What matters more: housing people, or padding profits? Drop your thoughts in the comments. #LoritaForSenate #AffordableHousingNow #PeopleOverProfit #VApolitics #RealPeopleRealPolicy #StopProject2025
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 44.9/100 |
| Spend / Reach / Long. / Eff. | 23.7 · 66.9 · 22.6 · 66.3 |
| Spend range | USD 400–499 |
| Impressions | 35,000 – 39,999 |
| CPM (≈ $/1k impr) | USD 11.99 |
| Est. audience size | — |
| Days live | 83 (2026-02-24 → 2026-05-18) |
| Created | 2026-02-24 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | VA — Lorita Daniels |
| Surfaced by | “senate:Lorita Daniels” |
🧠 AI analysis
| Issue | housing |
| Framing | contrast comparison |
| Message type | list building survey |
| Emotional appeal | anger |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | family, money cash |
| Call to action | survey poll |
| Standout element | split-panel contrast graphic pitting a modest family home against luxury high-rise construction |
| Tactic | The side-by-side 'This vs. That' visual and comment-bait CTA combine to generate engagement while framing the race as a moral choice between people and profit, efficiently harvesting audience sentiment for list-building. |
Where it ran (delivery by region)
| Virginia | 99.8% |
| North Carolina | 0.1% |
| Maryland | 0.1% |
| Washington, District of Columbia | 0.0% |
| New York | 0.0% |
| South Carolina | 0.0% |
| Tennessee | 0.0% |
Who saw it (delivery)
| 18-24 · female | 14.7% |
| 45-54 · male | 3.8% |
| 65+ · unknown | 0.1% |
| 65+ · male | 7.2% |
| 65+ · female | 5.0% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 4.8% |
| 55-64 · female | 2.7% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 1.9% |
| 18-24 · male | 23.4% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 6.4% |
| 35-44 · female | 3.2% |
| 25-34 · unknown | 0.5% |
| 25-34 · male | 16.5% |
| 25-34 · female | 8.3% |
| 18-24 · unknown | 1.1% |
| Unknown · male | 0.0% |
