David Costello US Inactive
COSTELLO FOR U.S. SENATE
Ad copy
Maine voters, let’s surprise the press and pundits tomorrow! Of the two CHANGE candidates on Maine’s US Senate primary ballot. One is well known yet suffers from having no substantive government experience and a raft of serious judgement lapses. And the other, me, is not well known, but benefits from having genuine, perspective honing working-class roots, a solid education, and extensive senior-level government experience in the US and abroad... AND know that if I were to surprise tomorrow, I’d have no trouble raising money and making the case that I have the energy and most fitting background, knowledge, and experience to defeat Susan Collins in November. So, to help in flipping control of the US Senate in 2027, rank me #1 on tomorrow’s Democratic primary ballot...
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Performance proxies
| Overall score | 35.0/100 |
| Spend / Reach / Long. / Eff. | 11.9 · 59.2 · 0.0 · 68.8 |
| Spend range | USD 100–199 |
| Impressions | 15,000 – 19,999 |
| CPM (≈ $/1k impr) | USD 8.54 |
| Est. audience size | 500,001 – 1,000,000 |
| Days live | 1 (2026-06-08 → 2026-06-09) |
| Created | 2026-06-08 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — David Costello |
| Surfaced by | “senate:David Costello” |
🧠 AI analysis
| Issue | candidate character bio |
| Framing | contrast comparison |
| Message type | persuasion |
| Emotional appeal | urgency |
| Production tier | diy amateur |
| Who pictured | candidate |
| Symbols | none |
| Call to action | vote |
| Standout element | Candidate speaking at podium with MAINE branding visible, projecting insider credibility |
| Tactic | Classic underdog contrast tactic — directly attacks the better-known opponent's qualifications while positioning himself as the experienced, authentic alternative, urging a primary day surprise. |
Where it ran (delivery by region)
| Maine | 81.6% |
| New Hampshire | 15.5% |
| Massachusetts | 2.8% |
| New Brunswick | 0.1% |
Who saw it (delivery)
| 18-24 · female | 19.3% |
| 45-54 · unknown | 0.1% |
| Unknown · female | 0.0% |
| 65+ · unknown | 0.1% |
| 65+ · male | 7.7% |
| 65+ · female | 9.3% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 4.9% |
| 55-64 · female | 4.3% |
| 45-54 · male | 3.5% |
| 18-24 · male | 17.6% |
| 45-54 · female | 2.7% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 4.6% |
| 35-44 · female | 3.7% |
| 25-34 · unknown | 0.5% |
| 25-34 · male | 11.1% |
| 25-34 · female | 9.4% |
| 18-24 · unknown | 1.1% |
| Unknown · male | 0.0% |
