Jon Ossoff US Inactive
JON OSSOFF FOR SENATE
Help Jon Fight Back
Ad copy
Not the news we were hoping to share, but here it goes… Jon’s new "MAGA Warrior” opponent is outspending us on TV. The truth is, he’s a megamillionaire who already spent over $2 MILLION in ad buys and is planning to spend MILLIONS more of his own money to try and flip this Senate seat. The U.S. Senate race in Georgia isn’t just another election. It’s the one race MAGA is banking on. Because they know that if they beat Jon, they’ll hold the Senate. We need your help fighting back and stopping a MAGA takeover in Georgia. Can you rush a donation to help defend this seat?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 62.5/100 |
| Spend / Reach / Long. / Eff. | 86.9 · 100.0 · 16.3 · 46.8 |
| Spend range | USD 150,000–174,999 |
| Impressions | 1,000,000 – 0 |
| CPM (≈ $/1k impr) | USD 162.5 |
| Est. audience size | — |
| Days live | 60 (2025-05-30 → 2025-07-29) |
| Created | 2025-05-30 |
| 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 | attack opponent |
| Message type | fundraising |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | opponent |
| Symbols | none |
| Call to action | donate |
| Standout element | Trump at a MAGA podium overlaid with opponent Buddy Carter's name in bold red, framing him as Trump's proxy |
| Tactic | Classic fear-and-urgency fundraising tactic: casts the opponent as a megamillionaire MAGA surrogate outspending Ossoff, using a video freeze-frame of Trump to tie Carter to an unpopular figure and drive emergency donations. |
Where it ran (delivery by region)
| Georgia | 15.0% |
| California | 14.7% |
| New York | 5.6% |
| Texas | 5.3% |
| Florida | 5.3% |
| Washington | 3.3% |
| North Carolina | 3.1% |
Who saw it (delivery)
| 18-24 · female | 2.8% |
| 45-54 · male | 5.8% |
| 65+ · male | 12.8% |
| 65+ · female | 23.9% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 8.1% |
| 55-64 · female | 12.5% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 7.7% |
| 18-24 · male | 2.6% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 5.2% |
| 35-44 · female | 6.8% |
| 25-34 · unknown | 0.2% |
| 25-34 · male | 4.7% |
| 25-34 · female | 5.6% |
| 18-24 · unknown | 0.3% |
| 65+ · unknown | 0.4% |
