Predicting Customer
Churn Webinar

Learn about the value of predicting customer churn rates with historical data

Recorded October 2017
In today's competitive market, maintaining a high customer retention rate is critical to success. Understanding when a customer may be at risk to break ties with your organization could help you take a more targeted approach to relationship management, effectively plan for future financial impact, and even prevent the loss of customers in the first place.   

Using the right tools, it is possible to proactively plan for customer churn by analyzing historical data from previous and existing clients. In the webinar recording below, we demonstrate the value of customer churn prediction as well as discuss how to accurately predict which customers are likely to turn over.

Additionally, we explore how data sets can be enriched to identify root causes of churn so that campaigns and conversations can be created to not only prevent churn, but also to potentially re-acquire dissatisfied customers.

Watch the recording now:

 
 
 
 
 
26:34
 
 
 
 
26:34
 
 
 
 
 
 
 
 
 
 
Wistia video thumbnail - Customer Churn - Oct 2017
 

Thanks for reporting a problem. We'll attach technical data about this session to help us figure out the issue. Which of these best describes the problem?

Any other details or context?

Cancel
message
 
 
 
Enter your name & email address
to view this webinar.
Error text
 
 
 
 
Edit
 
 

 

For more information on Customer Churn and how BlueGranite can help, check out our Customer Churn solution offering!

 Webinar GOALS

  • Discuss industry use cases for customer churn in retail, distribution, banking, and utilities environments

  • Learn how to utilize historic customer data for use in the churn prediction

  • Understand how to identify the root causes of churn and potentially prevent loss of customers

 Webinar Details

  • Recorded October 2017
  • Hosted using GoToWebinar - after registering you will receive a confirmation email with viewing instructions

PRESENTERS

Colby Ford
Data ScientistColbyFord (002).jpg

Coming from a background in mathematics, statistics, and bioinformatics, Colby combines this expertise to bring Data Science to everyone. He utilizes R and Python and puts Machine Learning to work to gain insight from data. Outside of BlueGranite, Colby is an avid pianist and genomics researcher. Check out Colby’s website at www.colbyford.com.

Barrie PikeBarriePike.png
Consultant

Barrie Pike is an accomplished executive with over 25 years’ 

experience in the technology industry specializing in building solutions and applications for consumer goods, retailers, and manufacturers. He is data driven with a deep focus on driving analytics into all aspects of the retail supply and demand chain. Currently, Barrie works as a consultant helping organizations transform their technical and business experience into rapidly deployable and repeatable solutions.

Have a question? 

REACH OUT TO US!

BLUEGRANITE HANDS-ON LABS

Utilities

Energy

Energy

How much energy should we generate next quarter to meet demand?

Water

Water

Based on previous usage history at this location, how many gallons of water with a new customer will likely use per month?

Fuel

Fuel

How will a cold Winter affect natural gas usage compared to the past few years?

demand-forecasting-icon-retail.png

Retail

Stock

Stock

How many of this item do I expect to sell this month?

Delievry

Delivery

Given that it takes a while to get a delivery, how much of each item should I order?

Customer Traffic

Customer Traffic

How many workers should I schedule based on projected customer traffic today?

demand-forecasting-icon-information-technology.png

Information Technology

Infastructure Utilization

Infastructure Utilization

What level of bandwidth utilization should we expect each day this month?

System Outages

System Outages

Given past history of outages, when is the next outage likely to occur?

Personnel Support

Personnel Support

Given the current trending numbers of employees, how many do we suspect we will have to support next year?