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Predicting Employee Churn with Data Mining

Use Data Mining to Identify Employees at Risk of Churn For organizations that have a lot employees that are in high turnover positions predicting employee churn with data mining can help to reduce and retain top talent.  By collecting data on employees and then building a predictive model using employees that have left the organization.  You can create models that will give you new insights into the characteristics of employees that are at risk of leaving.  By having this score you can then match up the performance of the employee to determine options to keep your talent and prevent them from leaving.  For example a call center, sales team, or temporary agencies could all benefit from building models to determine why employees are leaving. Build the Model For this example model, I used a sample dataset that contains various information for each employee.  This data contains both customers that are [...]

By |2017-05-11T19:01:44+00:00May 11th, 2017|Churn, Data Mining|0 Comments

Increase Revenue by Predicting Customer Churn

Value from Predicting Customer Churn Predicting customer churn allows businesses to leverage predictive analytics to classify customers based on how likely they are to churn.  You can divide your customers into segments or get as granular as calculating each customers probability of churn.  By using historical data from your operational systems you can mine the data to create predictive classifications.  Then using this information you can modify your operational processes to take advantage of this new insight and how best to handle your customer base customized to each customer.  While data quality is important, when you first get started building predictive modeling you should start with the data you have.  It is more important to build a model, filter out bad data, and learn about your data and how it can improve your operations. Using data from a fictitious telecommunication company.  You will see how data mining works to determine [...]

By |2017-01-18T08:11:51+00:00January 18th, 2017|Churn|0 Comments