JON OSSOFF FOR SENATE
All Eyes are on Georgi
All Eyes are on Georgi
It’s official: MAGA extremist Mike Collins is our opponent for U.S. Senate in Georgia. If everyone reading this chipped in just $20.26 right now, we'd have the resources to hold this seat and win back the Senate majority. But not everyone donates, so we need those who understand the stakes to give today. Can you rush a donation today?
It’s official: MAGA extremist Mike Collins is our opponent for U.S. Senate in Georgia. If everyone reading this chipped in just $20.26 right now, we'd have the resources to hold this seat and win back the Senate majority. But not everyone donates, so we need those who understand the stakes to give today. Can you rush a donation today?
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| Overall score | 57.4/100 |
| Spend / Reach / Long. / Eff. | 73.7 · 99.5 · 0.8 · 55.6 |
| Spend range | USD 45,000–49,999 |
| Impressions | 900,000 – 999,999 |
| CPM (≈ $/1k impr) | USD 50.0 |
| Est. audience size | — |
| Days live | 4 (2026-06-18 → 2026-06-22) |
| Created | 2026-06-16 |
| Creative variants | 2 body · 2 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | GA — Jon Ossoff |
| Surfaced by | “senate:Jon Ossoff” |
| Issue | democracy elections |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | money cash |
| Call to action | donate |
| Standout element | Bold '$269 million' in blue text on a red laptop screen — reframing a threatening dollar figure as a fundraising alarm |
| Tactic | Classic fear-and-urgency fundraising tactic that names the opponent as a 'MAGA extremist,' uses a specific small ask ($20.26) to lower the barrier to donate, and weaponizes a large opposition dollar figure to create donor urgency. |
| Georgia | 17.6% |
| California | 13.5% |
| New York | 7.5% |
| Florida | 5.5% |
| Texas | 4.2% |
| Massachusetts | 3.8% |
| Illinois | 3.6% |
| 18-24 · female | 0.2% |
| 45-54 · male | 6.0% |
| 65+ · male | 19.2% |
| 65+ · female | 32.6% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 10.7% |
| 55-64 · female | 13.0% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 6.1% |
| 18-24 · male | 0.3% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 4.3% |
| 35-44 · female | 3.3% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 1.9% |
| 25-34 · female | 1.4% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.6% |