Rachel Fetty Anderson for U.S. Senate US Inactive
Elect Fetty Anderson Senate Campaign
A Different Kind of Blue
Ad copy
Rachel Fetty Anderson is a public interest attorney with nearly 30 years of experience, working pro bono in family law, abuse and neglect cases, disability services, and benefits appeals. She is a foster and adoptive parent, a living organ donor, and a board member of several nonprofit organizations in her community. While running for U.S. Senate, Rachel has continued her pro bono legal work, coached bocce ball for the Special Olympics, and is an active volunteer with the United Way's 211 program, providing people in her community with food assistance, housing services, childcare, and elder care. Please consider donating to her grassroots campaign for U.S. Senate in West Virginia. Thank you.
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Performance proxies
| Overall score | 34.0/100 |
| Spend / Reach / Long. / Eff. | 11.9 · 55.8 · 1.9 · 66.3 |
| Spend range | USD 100–199 |
| Impressions | 10,000 – 14,999 |
| CPM (≈ $/1k impr) | USD 11.96 |
| Est. audience size | — |
| Days live | 8 (2026-06-17 → 2026-06-25) |
| Created | 2026-06-17 |
| Creative variants | 1 body · 1 headline |
| Platforms | |
| Languages | en |
| Candidate | WV — Rachel Fetty Anderson |
| Surfaced by | “senate:Rachel Fetty Anderson” |
🧠 AI analysis
| Issue | candidate character bio |
| Framing | positive candidate |
| Message type | persuasion |
| Emotional appeal | empathy |
| Production tier | diy amateur |
| Who pictured | candidate |
| Symbols | none |
| Call to action | donate |
| Standout element | Candidate speaking directly to camera in front of her own campaign yard sign, creating an intimate selfie-style introduction |
| Tactic | Classic bio-introduction tactic using rapid personal credential stacking — attorney, organ donor, foster parent, volunteer — to build maximum empathy and trust before making a donation ask. |
Where it ran (delivery by region)
| New York | 75.2% |
| California | 24.4% |
| New Mexico | 0.4% |
Who saw it (delivery)
| 18-24 · female | 0.1% |
| 45-54 · male | 4.6% |
| 65+ · male | 34.9% |
| 65+ · female | 30.5% |
| 55-64 · unknown | 0.2% |
| 55-64 · male | 12.9% |
| 55-64 · female | 7.0% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 2.5% |
| 18-24 · male | 0.2% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 2.6% |
| 35-44 · female | 1.3% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 1.8% |
| 25-34 · female | 0.8% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.5% |
