Jordan Wood US Inactive
JORDAN FOR MAINE
Will you chip in to help me defeat Susan Collins?
Will you chip in to help me defeat Susan Collins?
Can I count on your $10? >>
Can I count on your $10? >>
Ad copy
I watched Susan Collins advance Trump's cruel budget to the Senate floor – now, we need to make her regret it. I’m within one point of winning. So I’m asking for a massive surge of donations in response to her vote to help me defeat her and ensure she can never do this again.
I watched Susan Collins advance Trump's cruel budget to the Senate floor – now, we need to make her regret it. I’m within one point of winning. So I’m asking for a massive surge of donations in response to her vote to help me defeat her and ensure she can never do this again.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 40.4/100 |
| Spend / Reach / Long. / Eff. | 31.7 · 63.8 · 7.7 · 58.4 |
| Spend range | USD 900–999 |
| Impressions | 25,000 – 29,999 |
| CPM (≈ $/1k impr) | USD 34.53 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 29 (2025-07-02 → 2025-07-31) |
| Created | 2025-07-02 |
| Creative variants | 2 body · 2 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Jordan Wood |
| Surfaced by | “senate:Jordan Wood” |
🧠 AI analysis
| Issue | economy taxes |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | anger |
| Production tier | diy amateur |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Candidate filming himself outdoors on a rocky Maine coastline in a casual fleece jacket, creating an urgent grassroots confessional feel |
| Tactic | Combines a specific triggering event (Collins's budget vote), a tight poll margin ('within one point'), and a direct dollar ask to manufacture urgency and convert anger into immediate donations. |
Where it ran (delivery by region)
| Maine | 100.0% |
Who saw it (delivery)
| 25-34 · female | 1.3% |
| 25-34 · male | 0.6% |
| 25-34 · unknown | 0.1% |
| 35-44 · female | 4.1% |
| 35-44 · male | 1.9% |
| 35-44 · unknown | 0.2% |
| 45-54 · female | 7.8% |
| 45-54 · male | 2.9% |
| 45-54 · unknown | 0.2% |
| 55-64 · female | 18.9% |
| 55-64 · male | 7.0% |
| 55-64 · unknown | 0.3% |
| 65+ · female | 38.6% |
| 65+ · male | 15.1% |
| 65+ · unknown | 0.9% |
