How to Use Dynamic Topic Modeling to Boost Your Marketing and Strategy

Episode Summary:

In this episode, Mukundan simplifies the concept of Dynamic Topic Modeling (DTM) for listeners and discusses its transformative impact on businesses. DTM is a machine learning method used to track the evolution of themes in text data over time. It helps companies to make smarter decisions by staying in tune with customer needs and market trends.

Key Topics Covered:

1. Introduction to Dynamic Topic Modeling

   • What it is and why it matters for businesses.

   • Real-world examples like customer reviews and social media trends.

2. How Dynamic Topic Modeling Works

   • Over time, analyze text data (e.g., reviews, surveys, reports).

   • Groups words into topics such as price, quality, or features.

3. Applications of Dynamic Topic Modeling

   • Adjusting marketing strategies to customer priorities.

   • Enhancing product features based on evolving feedback.

   • Predicting and responding to trends like sustainability in physical products.

   • Tracking employee feedback to refine HR strategies and reduce churn.

4. Step-by-Step Guide to Implementing DTM

   • Collecting text data (e.g., reviews, surveys).

   • Using tools like Python or pre-built software for analysis.

   • Generating clear visuals and actionable insights.

5. Benefits for Businesses

   • Understanding customer and employee feedback more effectively.

   • Staying ahead of competitors.

   • Saving time while making informed, data-driven decisions.

6. Call to Action

   • Encourage listeners to explore DTM to gain a competitive edge.

   • Mukundan invites questions and collaboration via email: mukundansankar.substack.com.

Memorable Quotes:

• "Dynamic Topic Modeling helps businesses turn text data into actionable business strategies."

• "With DTM, you can stay ahead of competitors by understanding what customers truly care about over time."

• "It's not just about making decisions but smarter decisions driven by data."

Real-Life Examples:

• Amazon Reviews: How DTM categorizes feedback into price, durability, and other topics.

• Marketing Adjustments: Shifting focus to features customers prioritize.

• Trend Analysis: Tracking the rise of sustainability in customer demands.

• Employee Insights: Using DTM to predict trends in employee satisfaction and churn.

Resources Mentioned:

• Dynamic Topic Modeling Tools: Python and other software solutions for beginners and professionals.

• Email for Guidance: mukundansankar.substack.com