Susan Collins US Inactive
COLLINS FOR SENATOR
Ad copy
I appreciate that the WGME CBS 13 News, Portland #ITEAM made the effort to investigate this important issue. Because of their research, we now know that the Veterans Crisis Hotline may not always be able to immediately locate veterans who call or text during a time of crisis. I have asked the Secretary of Veterans Affairs to determine what tools or resources are needed to properly help all veterans during their darkest time of need. We must make sure that when our servicemen and women return home, they are well supported.
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Performance proxies
| Overall score | 40.1/100 |
| Spend / Reach / Long. / Eff. | 21.0 · 69.3 · 0.0 · 70.0 |
| Spend range | USD 300–399 |
| Impressions | 45,000 – 49,999 |
| CPM (≈ $/1k impr) | USD 7.36 |
| Est. audience size | — |
| Days live | 1 (2020-02-26 → 2020-02-27) |
| Created | 2020-02-25 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Susan Collins |
| Surfaced by | “senate:Susan Collins” |
🧠 AI analysis
| Issue | veterans |
| Framing | issue advocacy |
| Message type | awareness |
| Emotional appeal | empathy |
| Production tier | semi pro |
| Who pictured | veterans military |
| Symbols | military |
| Call to action | none |
| Standout element | Glowing blue US map graphic behind a TV news reporter, lending local news credibility to the issue |
| Tactic | Collins borrows the credibility of a local CBS investigative news report to position herself as a responsive advocate for veterans in crisis, building trust through third-party validation rather than direct campaigning. |
Where it ran (delivery by region)
| Maine | 100.0% |
Who saw it (delivery)
| 65+ · male | 11.7% |
| 18-24 · male | 1.3% |
| 25-34 · unknown | 0.0% |
| 35-44 · unknown | 0.1% |
| 55-64 · unknown | 0.1% |
| 65+ · unknown | 0.1% |
| 45-54 · unknown | 0.1% |
| 18-24 · female | 0.4% |
| 35-44 · female | 3.3% |
| 25-34 · female | 1.6% |
| 45-54 · female | 7.0% |
| 25-34 · male | 5.8% |
| 55-64 · female | 14.0% |
| 45-54 · male | 12.4% |
| 65+ · female | 20.7% |
| 35-44 · male | 7.9% |
| 55-64 · male | 13.4% |
| 18-24 · unknown | 0.0% |
