Jon Ossoff US Inactive
JON OSSOFF FOR SENATE
Help Jon Fight Back
Stop Marjorie Taylor Greene from becoming a U.S. Senator.
Ad copy
***Please stop scrolling and read this*** Jon Ossoff is being bombarded with right-wing attack ads in Georgia & our MAGA opponent is outspending us on TV. Jon needs your help to fight back and defend this seat. Can you rush a donation before our fundraising deadline to help us fight back?
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 59.9/100 |
| Spend / Reach / Long. / Eff. | 85.1 · 100.0 · 6.3 · 48.1 |
| Spend range | USD 125,000–149,999 |
| Impressions | 1,000,000 – 0 |
| CPM (≈ $/1k impr) | USD 137.5 |
| Est. audience size | — |
| Days live | 24 (2025-06-30 → 2025-07-24) |
| Created | 2025-06-30 |
| 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 | money cash |
| Call to action | donate |
| Standout element | Retro CRT TV displaying opponent posing with Trump, framed as a threat broadcasting into living rooms |
| Tactic | Classic underdog fundraising tactic — pairing a deadline urgency with a villain-framing device (old TV showing Trump-tied opponent) to trigger fear-based small-dollar donations before an artificial deadline. |
Where it ran (delivery by region)
| California | 15.9% |
| Georgia | 15.5% |
| Texas | 6.4% |
| New York | 6.0% |
| Florida | 5.5% |
| North Carolina | 3.2% |
| Illinois | 3.0% |
Who saw it (delivery)
| 18-24 · female | 3.3% |
| 45-54 · male | 6.5% |
| 65+ · male | 7.8% |
| 65+ · female | 16.9% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 6.5% |
| 55-64 · female | 11.6% |
| 45-54 · unknown | 0.2% |
| 45-54 · female | 10.6% |
| 18-24 · male | 3.4% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 7.5% |
| 35-44 · female | 10.2% |
| 25-34 · unknown | 0.2% |
| 25-34 · male | 7.0% |
| 25-34 · female | 7.6% |
| 18-24 · unknown | 0.2% |
| 65+ · unknown | 0.3% |
