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How To Predict Customer Churn With Data

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Manage episode 464755445 series 3629438
Content provided by Roman Villard. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Roman Villard or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

On today’s episode of Data Fuel, we explore how SMBs can use data to predict and prevent customer churn. Learn how to identify churn signals, build a churn prediction model, and implement insights into your daily operations. By proactively managing customer retention, your business can reduce churn, improve loyalty, and increase revenue.

Main Topics:

• Why customer churn prediction is the easiest entry point for data science.

• How churn indicators differ by industry.

• Step-by-step guide to building a churn prediction model.

• How to tag customers and personalize retention strategies.

• Avoiding common pitfalls in churn prediction.

Connect with us!
Website
LinkedIn

  continue reading

10 episodes

Artwork
iconShare
 
Manage episode 464755445 series 3629438
Content provided by Roman Villard. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Roman Villard or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

On today’s episode of Data Fuel, we explore how SMBs can use data to predict and prevent customer churn. Learn how to identify churn signals, build a churn prediction model, and implement insights into your daily operations. By proactively managing customer retention, your business can reduce churn, improve loyalty, and increase revenue.

Main Topics:

• Why customer churn prediction is the easiest entry point for data science.

• How churn indicators differ by industry.

• Step-by-step guide to building a churn prediction model.

• How to tag customers and personalize retention strategies.

• Avoiding common pitfalls in churn prediction.

Connect with us!
Website
LinkedIn

  continue reading

10 episodes

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