Naomi Parris

Assistant Editor, Shopping

Preston's Summary

Naomi Parris is the assistant shopping editor at PS, based in New York. With over eight years of experience, she specializes in storytelling that merges fashion, beauty, and Black culture, contributing to notable publications such as Essence, Elle, and Bustle. Naomi's work has been featured in various outlets including Popsugar Inc and Essence, while her personal blog 'Eli-Nay' showcases her passion for style guides and cultural pieces.

Preston is the artificial intelligence that powers the Intelligent Relations PR platform. Meet Preston

Geo Focus

Guyana (National)

Coverage Attributes:

Beta
Informative: 47 %
Data Driven: 11 %
Interviews Q&as: 11 %
Events: 7 %
Promotional: 6 %

Themes Covered:

Not enough data icon

Not enough data

Most Recent Topics:

  • AgriTech (agricultural technology)
  • Agroecology
  • Sustainable Agriculture
  • Environmental Services
  • Forestry
  • Natural Resources
  • Farm Management
  • Farming Equipment

Pitching Insights

Naomi Parris focuses heavily on beauty and fashion content, including reviews, event coverage, promotional deals, and profile features. Her articles cover makeup trends, fashion events, celebrity interviews related to style and appearance.

Given her focus on beauty & fashion with a national (United States) geographic scope in mind for some of the pieces she writes about celebrities' fashion moments or products that have gone viral on platforms like TikTok. Therefore Naomi is likely to be interested in pitches centered around emerging beauty and fashion trends in the US market.

If you're looking to pitch to Naomi Parris consider offering insights into new product launches or collaborations within the beauty industry or providing access to high-profile individuals who can speak authoritatively about their experiences with prominent brands or designers.

This information evolves through artificial intelligence and human feedback. Improve this profile .

Journalists With Similar Coverage:

Based on similarity of content.
Publications
Most recent topics
Not enough data
Most recent topics
Not enough data
Most recent topics
Not enough data
Most recent topics
Not enough data
Publications
Most recent topics
Not enough data
Publications
Most recent topics
Not enough data