Ed Markey US Inactive
THE MARKEY COMMITTEE
Rush a Contribution
Please contribute to our grassroots campaign today
Ad copy
With just a few days to go, Joe Kennedy’s super PAC and his big money backers have spent a staggering $7 MILLION on TV ads to try and stop us. But we’ve got news for them: we aren't going to let them buy this seat. Can we count on you to rush a donation to our campaign in the final stretch? Let’s show them that no amount of big money is as powerful as our grassroots campaign.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 43.2/100 |
| Spend / Reach / Long. / Eff. | 38.3 · 72.4 · 1.9 · 60.3 |
| Spend range | USD 1,500–1,999 |
| Impressions | 60,000 – 69,999 |
| CPM (≈ $/1k impr) | USD 26.92 |
| Est. audience size | — |
| Days live | 8 (2020-08-23 → 2020-08-31) |
| Created | 2020-08-23 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | MA — Ed Markey |
| Surfaced by | “senate:Ed Markey” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | contrast comparison |
| Message type | fundraising |
| Emotional appeal | urgency |
| Production tier | semi pro |
| Who pictured | candidate |
| Symbols | money cash |
| Call to action | donate |
| Standout element | direct-to-camera candidate appeal with grassroots vs. big money contrast framing |
| Tactic | Classic David-vs-Goliath fundraising tactic that weaponizes opponent's spending as evidence of threat, converting donor anxiety into urgent small-dollar action. |
Where it ran (delivery by region)
| California | 23.2% |
| New York | 12.3% |
| Washington | 4.6% |
| Illinois | 3.7% |
| Pennsylvania | 3.5% |
| Texas | 3.5% |
| Florida | 3.4% |
Who saw it (delivery)
| 25-34 · unknown | 0.3% |
| 65+ · female | 22.3% |
| 35-44 · unknown | 0.3% |
| 18-24 · female | 0.6% |
| 25-34 · male | 5.1% |
| 25-34 · female | 2.0% |
| 55-64 · unknown | 0.5% |
| 45-54 · male | 6.7% |
| 65+ · unknown | 0.7% |
| 45-54 · unknown | 0.3% |
| 65+ · male | 22.4% |
| 55-64 · female | 11.4% |
| 55-64 · male | 12.6% |
| 35-44 · male | 5.8% |
| 45-54 · female | 4.5% |
| 18-24 · male | 1.4% |
| 35-44 · female | 3.2% |
| 18-24 · unknown | 0.1% |
