Jon Ossoff US Inactive
JON OSSOFF FOR SENATE
Help Jon Fight Back
Stop Marjorie Taylor Greene from becoming a U.S. Senator.
Ad copy
This is difficult to share, but recent polling shows Jon Ossoff statistically tied with his MAGA loyalist opponent, Mike Collins. To make things worse, far-right Super PACs are spending MILLIONS of dollars to try and flip this seat. The campaign will be brutal, and Jon certainly can't do this alone. But our team wins the toughest battles. Together, we flipped Georgia when no one thought it was possible. And we will win again — with your help. So please, chip in $5, $15 or anything you can towards Jon's reelection campaign today.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 58.7/100 |
| Spend / Reach / Long. / Eff. | 75.3 · 100.0 · 4.4 · 54.9 |
| Spend range | USD 50,000–59,999 |
| Impressions | 1,000,000 – 0 |
| CPM (≈ $/1k impr) | USD 55.0 |
| Est. audience size | — |
| Days live | 17 (2025-09-15 → 2025-10-02) |
| Created | 2025-09-15 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | GA — Jon Ossoff |
| Surfaced by | “senate:Jon Ossoff” |
🧠 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 | Side-by-side poll bar chart showing Ossoff and Collins nearly tied, with Trump's image paired next to Collins |
| Tactic | Classic fundraising fear-and-urgency tactic using a real poll to manufacture closeness anxiety, framing the ask as a defensive necessity against MAGA Super PAC spending. |
Where it ran (delivery by region)
| Georgia | 14.8% |
| California | 14.8% |
| New York | 6.5% |
| Texas | 5.1% |
| Florida | 4.5% |
| Illinois | 3.7% |
| Massachusetts | 3.5% |
Who saw it (delivery)
| 18-24 · female | 1.2% |
| 45-54 · male | 6.3% |
| 65+ · male | 9.3% |
| 65+ · female | 22.5% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 7.0% |
| 55-64 · female | 13.5% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 11.2% |
| 18-24 · male | 0.9% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 6.5% |
| 35-44 · female | 10.4% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 4.0% |
| 25-34 · female | 6.1% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.4% |
