Personalized Public Relations Through Machine Learning

Objectives:

• Understand the role of machine learning in modern public relations.
• Learn how machine learning algorithms can personalize communication strategies.
• Explore data-driven decision-making in public relations.
• Apply machine learning tools to enhance public relations efforts and strategies.

Introduction to Machine Learning and Public Relations

• Overview of public relations and its evolving landscape.
• Basics of machine learning and its applications in various industries.
• How machine learning is transforming PR practices.
• Key benefits of integrating machine learning into PR campaigns.

Data Collection and Analysis for Personalized PR

• Importance of data in public relations.
• Types of data relevant to public relations (social media, surveys, etc.).
• Methods for collecting and cleaning data for analysis.
• How to use machine learning for data-driven PR strategies.

Machine Learning Algorithms in Public Relations

• Overview of machine learning algorithms used in PR (e.g., natural language processing, recommendation systems).
• How algorithms can segment audiences and tailor content.
• Case studies of machine learning in successful PR campaigns.
• Tools and platforms for implementing machine learning in PR.

Implementing Machine Learning for PR Campaigns

• Steps to create a personalized PR strategy using machine learning.
• Best practices for integrating machine learning into PR workflows.
• Monitoring and measuring the success of machine learning-based PR campaigns.
• Future trends in personalized public relations through machine learning.

DATE:
1ST BATCH: 7th – 10th Apr, 2026
2ND BATCH: 28th – 31st July, 2026
3RD BATCH: 24th- 27th Nov, 2026