Tamika Lyles US Inactive
Tamika Lyles Gillispie
I decided to #RunWithTamika!!!
Join us & Contribute Today!!!
Ad copy
As we sit in quarantine, it’s a great time to research current candidates and identify the people who are TRULY fighting for the people. As a Mother, Educator (proud Union member), Veteran (USAF), and Advocate in the community, my desire to go to Tallahassee is just a larger step in my advocacy and my oath of service to this country/community. I invite you to discover more about me at www.LylesforHD43.com and contribute using the link below.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 28.1/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 45.5 · 0.0 · 67.0 |
| Spend range | <USD 99 |
| Impressions | 4,000 – 4,999 |
| CPM (≈ $/1k impr) | USD 11.0 |
| Est. audience size | — |
| Days live | 1 (2020-03-20 → 2020-03-21) |
| Created | 2020-03-20 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | FL — Tamika Lyles |
| Surfaced by | “senate:Tamika Lyles” |
🧠 AI analysis
| Issue | candidate character bio |
| Framing | positive candidate |
| Message type | fundraising |
| Emotional appeal | pride |
| Production tier | semi pro |
| Who pictured | veterans military |
| Symbols | farm rural, military |
| Call to action | donate |
| Standout element | Bold blue-on-blue candidate name logo flanked by Florida orange blossom and orange fruit imagery evoking local Florida identity |
| Tactic | The ad leverages identity stacking — Mother, Educator, Union Member, Veteran, Advocate — to build multi-dimensional relatability and credibility across several key Democratic voter blocs while using ActBlue's donation link to convert awareness into fundraising. |
Where it ran (delivery by region)
| Florida | 100.0% |
Who saw it (delivery)
| 65+ · female | 1.0% |
| 45-54 · male | 0.6% |
| 35-44 · unknown | 0.0% |
| 18-24 · unknown | 0.2% |
| 55-64 · unknown | 0.0% |
| 65+ · male | 0.4% |
| 25-34 · unknown | 0.3% |
| 55-64 · male | 0.3% |
| 55-64 · female | 0.4% |
| 25-34 · male | 12.0% |
| 45-54 · female | 1.3% |
| 25-34 · female | 20.3% |
| 35-44 · female | 2.7% |
| 18-24 · male | 18.9% |
| 35-44 · male | 1.6% |
| 18-24 · female | 39.9% |
| 45-54 · unknown | 0.1% |
