Jessica Cherner is an Associate Shopping Editor at House Beautiful. She specializes in topics related to home and garden, house design, and interior design, with a keen focus on architecture, lifestyle, and retail trends. Jessica's work has been featured in notable publications such as Goyal & Co., New York Post, Yahoo News, and Architectural Digest.
Jessica Cherner
Associate Shopping Editor, House Beautiful
Preston's Summary
Preston is the artificial intelligence that powers the Intelligent Relations PR platform. Meet Preston
Geo Focus
United States (National)
Coverage Attributes:
Beta
Informative:
29
%
Reviews:
28
%
Listicles:
15
%
Opinion:
12
%
Promotional:
10
%
Themes Covered:
Not enough data
Pitching Insights
Jessica Cherner's coverage largely revolves around house and home topics, specifically focusing on architecture, furniture, home decor, shopping, and holidays. Given the high percentage of promotional deal articles in her coverage attributes, she may be particularly interested in pitches related to new product launches or unique promotions within the house and home space.
Considering her focus on seasonal content and gift guides as well as what readers are buying most often from specific outlets such as Williams Sonoma or House Beautiful suggests that she would likely appreciate pitches related to trending products for different seasons or occasions.
As there is no specified geographic focus for Jessica's work, it appears that she covers a broad international scope when it comes to house and home topics.
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
Publications
Most recent topics
Not enough data
Freelance Lifestyle Journalist
Publications
Most recent topics
Not enough data
Assistant Editor
Publications
Most recent topics
Not enough data
Contributor
Publications
Most recent topics
Not enough data
