Shawna Hudson

Associate Beauty Editor

Preston's Summary

Shawna Hudson is an Associate Beauty Editor for various publications, including Who What Wear, Newswav, and Sweety High Media. With a focus on skincare, haircare, and beauty trends, Shawna provides insightful articles and recommendations to help readers make informed choices in their beauty routines. Her work has also been featured in Who What Wear UK.

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

Geo Focus

Coverage Attributes:

Beta
Promotional Deal: 37 %
Review: 28 %
Gift Guides: 9 %
Seasonal: 6 %
How To Guide: 6 %

Themes Covered:

Not enough data icon

Not enough data

Most Recent Topics:

  • Beauty Industry
  • Hair
  • Hair Care Industry
  • Makeup & Skincare
  • Perfume & Fragrance
  • Wellness Programs

Pitching Insights

Shawna's articles predominantly focus on beauty and skincare, with a strong emphasis on product reviews, promotional deals, and gift guides. If you have new beauty or skincare products that are unique and effective, offering them for review or inclusion in a gift guide could be an effective way to reach out.

Given the nature of Shawna’s coverage, providing samples of your beauty or skincare products along with concise information about their benefits may increase the likelihood of her considering them for review.

As she covers various aspects of beauty including makeup, perfume, haircare etc., tailor your pitches according to the specific topic being covered in her recent articles.

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
Publications
Most recent topics
Not enough data
Valeriya Chupinina
Managing Editor, Trending Commerce Writer, Writer
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