Juliana Stratton US Inactive
JULIANA FOR ILLINOIS
Trump advisors are funding my Democratic opponent’s campaign!
Juliana is taking her fight for working families to Washington. Show your support by contributing to her grassroots campaign today.
Ad copy
URGENT! MAGA donors are buying out my Democratic opponent. Illinois deserves a leader who will fight relentlessly for working people — someone who can’t be bought by corporate PACs or MAGA donors. I will be that leader but I need your help getting there. Can you rush a donation and help me fight back? With less than 100 days left until our primary, your support has never been more important.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 31.5/100 |
| Spend / Reach / Long. / Eff. | 17.4 · 49.2 · 1.9 · 57.6 |
| Spend range | USD 200–299 |
| Impressions | 6,000 – 6,999 |
| CPM (≈ $/1k impr) | USD 38.39 |
| Est. audience size | — |
| Days live | 8 (2025-12-09 → 2025-12-17) |
| Created | 2025-12-09 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | IL — Juliana Stratton |
| Surfaced by | “senate:Juliana Stratton” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate, opponent |
| Symbols | none |
| Call to action | donate |
| Standout element | Chicago Sun-Times headline screenshot accusing Democratic opponent of taking MAGA donor money, juxtaposed with side-by-side candidate photos |
| Tactic | The ad weaponizes a credible newspaper headline to frame a Democrat-vs-Democrat primary attack, creating urgency by casting the opponent as secretly MAGA-funded to drive small-dollar donations. |
Where it ran (delivery by region)
| Illinois | 16.5% |
| California | 9.2% |
| Texas | 5.9% |
| New York | 5.2% |
| Florida | 4.5% |
| Pennsylvania | 3.6% |
| Michigan | 3.5% |
Who saw it (delivery)
| 18-24 · female | 0.1% |
| 45-54 · male | 4.7% |
| 65+ · male | 23.7% |
| 65+ · female | 32.5% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 9.7% |
| 55-64 · female | 11.5% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 5.7% |
| 18-24 · male | 0.3% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 3.8% |
| 35-44 · female | 3.3% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 2.1% |
| 25-34 · female | 1.3% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.5% |
