MARQUITA BRADSHAW FOR U S SENATE
Even though we can’t gather in crowds, climate activists can organize for real change.
"By the end of 1970, the U.S. had an Environmental Protection Agency and a Clean Air Act. The next few years brought landmark legislation to clean up rivers and lakes, regulate waste disposal and protect drinking water.” When we show up for the things we believe in, people listen – politicians listen. I intend to show up for you and advocate for a safer and cleaner environment. 🌎 #EarthDay reminds us how precious our planet is and why every decision we make must be made with sustainability in mind. Let’s win this together – https://secure.actblue.com/donate/marquita4us. 🗳 #Bradshaw2020 #MBforUS #95TNUSSen
↗ View in Meta Ad Library (the live creative — image/video/layout)
| Overall score | 30.0/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 49.2 · 1.1 · 69.7 |
| Spend range | <USD 99 |
| Impressions | 6,000 – 6,999 |
| CPM (≈ $/1k impr) | USD 7.62 |
| Est. audience size | — |
| Days live | 5 (2020-04-22 → 2020-04-27) |
| Created | 2020-04-22 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | TN — Marquita Bradshaw |
| Surfaced by | “senate:Marquita Bradshaw” |
| Issue | energy environment |
| Framing | issue advocacy |
| Message type | persuasion |
| Emotional appeal | hope |
| Production tier | semi pro |
| Who pictured | diverse crowd |
| Symbols | none |
| Call to action | donate |
| Standout element | sweeping black-and-white archival photo of the massive original 1970 Earth Day crowd, evoking historic grassroots power |
| Tactic | The ad leverages a historical Washington Post article and iconic archival protest imagery to draw a direct line between the environmental movement's past legislative victories and the candidate's present campaign, using nostalgia and collective empowerment to inspire both donations and civic engagement. |
| Tennessee | 100.0% |
| 65+ · male | 3.5% |
| 25-34 · unknown | 0.3% |
| 18-24 · unknown | 0.2% |
| 35-44 · unknown | 0.1% |
| 45-54 · unknown | 0.1% |
| 45-54 · male | 2.2% |
| 35-44 · female | 3.2% |
| 65+ · female | 3.5% |
| 55-64 · male | 3.5% |
| 55-64 · female | 2.8% |
| 45-54 · female | 1.8% |
| 25-34 · female | 23.5% |
| 25-34 · male | 11.1% |
| 18-24 · female | 32.8% |
| 35-44 · male | 1.9% |
| 18-24 · male | 9.5% |
| 65+ · unknown | 0.1% |