David Costello US Inactive
COSTELLO FOR U.S. SENATE
Ad copy
I worked for USAID in such shattered countries as Cambodia, Haiti, Bosnia, and Kosovo. USAID aid benefited US interests and saved countless lives there and elsewhere around the world. That’s what we, the USA, should best be known for – saving and improving lives. Senator Susan Collins was wrong to not fight for USAID!
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 37.2/100 |
| Spend / Reach / Long. / Eff. | 11.9 · 63.8 · 1.1 · 72.2 |
| Spend range | USD 100–199 |
| Impressions | 25,000 – 29,999 |
| CPM (≈ $/1k impr) | USD 5.44 |
| Est. audience size | 500,001 – 1,000,000 |
| Days live | 5 (2026-06-04 → 2026-06-09) |
| Created | 2026-06-04 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — David Costello |
| Surfaced by | “senate:David Costello” |
🧠 AI analysis
| Issue | foreign policy defense |
| Framing | contrast comparison |
| Message type | persuasion |
| Emotional appeal | empathy |
| Production tier | diy amateur |
| Who pictured | candidate, diverse crowd |
| Symbols | none |
| Call to action | none |
| Standout element | vintage snapshot of candidate crouching warmly among a group of smiling children abroad, evoking authentic humanitarian service |
| Tactic | The ad leverages personal humanitarian biography and an authentic old photograph to establish moral credibility, then pivots to attack Collins for failing to defend USAID, contrasting Costello's lived service with her inaction. |
Where it ran (delivery by region)
| Maine | 80.1% |
| New Hampshire | 16.6% |
| Massachusetts | 3.1% |
| New Brunswick | 0.1% |
Who saw it (delivery)
| 18-24 · female | 28.3% |
| 45-54 · male | 2.4% |
| 65+ · unknown | 0.1% |
| 65+ · male | 5.2% |
| 65+ · female | 6.0% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 3.1% |
| 55-64 · female | 2.9% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 2.2% |
| 18-24 · male | 18.9% |
| 35-44 · unknown | 0.0% |
| 35-44 · male | 3.9% |
| 35-44 · female | 3.0% |
| 25-34 · unknown | 0.8% |
| 25-34 · male | 9.9% |
| 25-34 · female | 11.1% |
| 18-24 · unknown | 2.0% |
| Unknown · male | 0.0% |
