Shannon Bray for North Carolina US Inactive
FRIENDS OF SHANNON BRAY
⚠ Creative removed by Meta
This ad's image was taken down for violating Meta's ad standards; the copy below is preserved from the Ad Library.
This ad's image was taken down for violating Meta's ad standards; the copy below is preserved from the Ad Library.
Shannon Bray for North Carolina
Running for US Senate (NC) in 2020
Ad copy
I'm running against Thom Tillis for the US Senate and can use your vote. Let's send Thom home for a well-deserved term-limit. #NCFirst #NCSen
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 34.0/100 |
| Spend / Reach / Long. / Eff. | 11.9 · 55.8 · 2.2 · 66.3 |
| Spend range | USD 100–199 |
| Impressions | 10,000 – 14,999 |
| CPM (≈ $/1k impr) | USD 11.96 |
| Est. audience size | — |
| Days live | 9 (2019-12-17 → 2019-12-26) |
| Created | 2019-12-17 |
| Creative variants | 1 body · 1 headline |
| Platforms | |
| Languages | en |
| Candidate | NC — Shannon Bray |
| Surfaced by | “senate:Shannon Bray” |
🧠 AI analysis
| Issue | democracy elections |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | urgency |
| Production tier | diy amateur |
| Who pictured | candidate |
| Symbols | none |
| Call to action | vote |
| Standout element | Facebook content removal notice repurposed as the ad creative itself, highlighting platform censorship |
| Tactic | The ad leverages a Facebook policy removal notice as a grassroots credibility signal, implying the candidate is being silenced by big tech to generate sympathy and urgency among anti-establishment voters. |
Where it ran (delivery by region)
| North Carolina | 100.0% |
Who saw it (delivery)
| 25-34 · unknown | 0.2% |
| 65+ · male | 7.0% |
| 35-44 · unknown | 0.2% |
| 55-64 · unknown | 0.2% |
| 18-24 · unknown | 0.1% |
| 45-54 · unknown | 0.2% |
| 18-24 · female | 1.4% |
| 35-44 · female | 6.8% |
| 45-54 · female | 10.0% |
| 18-24 · male | 2.9% |
| 55-64 · female | 13.5% |
| 45-54 · male | 11.6% |
| 65+ · female | 11.4% |
| 55-64 · male | 11.2% |
| 35-44 · male | 10.3% |
| 25-34 · male | 8.7% |
| 25-34 · female | 4.1% |
| 65+ · unknown | 0.1% |
