Shivam Gulati

Editor

AS SEEN ON

Preston's Summary

Shivam Gulati is an Editor for DualShockers, a gaming news and reviews website. With a focus on the gaming industry, Shivam covers a wide range of topics including game releases, updates, and spoilers, as well as providing editor picks for the site's annual Game of the Year selection.

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

Coverage Attributes:

Beta
How To Guide: 37 %
Review: 25 %
Event Coverage: 16 %
Seasonal: 8 %
Promotional Deal: 8 %

Themes Covered:

Not enough data icon

Not enough data

Most Recent Topics:

  • Video Games
  • Mobile Gaming
  • Controller Support
  • Online Games
  • Gaming Tips
  • Anime/Manga

Pitching Insights

Shivam Gulati's coverage focuses on entertainment, particularly anime, manga, and video games. He seems to be interested in event coverage and release dates within this space. If you have insights into upcoming releases or events related to anime, manga, or video games that align with his focus, he may be receptive to pitches about these topics.

Given his interest in the most anticipated games and series as well as spoilers for ongoing shows like Jujutsu Kaisen and Attack on Titan, providing exclusive information about highly-anticipated future releases or insider knowledge could capture Shivam's attention.

As there is no specific geographic focus mentioned for Shivam Gulati’s coverage attributes are not directly relevant but it appears that he has an international scope when it comes to entertainment news.

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

Journalists With Similar Coverage:

Based on similarity of content.
Ashish Jha
Deputy Copy Editor
Most recent topics
Not enough data
Nutan Lele
Associate - Content Operations
Publications
Most recent topics
Not enough data
Publications
Most recent topics
Not enough data
Publications
Most recent topics
Not enough data
Publications
Most recent topics
Not enough data