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Machine Learning for Marketing Analytics in R

In this course you'll learn how to use data science for several common marketing tasks.

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4 Hours17 Videos60 Exercises
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Course Description

This is your chance to dive into the worlds of marketing and business analytics using R. Day by day, there are a multitude of decisions that companies have to face. With the help of statistical models, you're going to be able to support the business decision-making process based on data, not your gut feeling. Let us show you what a great impact statistical modeling can have on the performance of businesses. You're going to learn about and apply strategies to communicate your results and help them make a difference.
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In the following Tracks

Marketing Analytics with R

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  1. 1

    Modeling Customer Lifetime Value with Linear Regression

    Free

    How can you decide which customers are most valuable for your business? Learn how to model the customer lifetime value using linear regression.

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    Customer lifetime value in CRM
    50 xp
    Benefits of knowing CLV
    50 xp
    Looking at data
    100 xp
    Simple linear regression
    50 xp
    Understanding residuals
    50 xp
    Estimating simple linear regression
    100 xp
    Multiple linear regression
    50 xp
    Avoiding multicollinearity
    100 xp
    Interpretation of coefficients
    50 xp
    Model validation, model fit, and prediction
    50 xp
    Interpretation of model fit
    50 xp
    Future predictions of sales
    100 xp
  2. 4

    Reducing Dimensionality with Principal Component Analysis

    CRM data can get very extensive. Each metric you collect could carry some interesting information about your customers. But handling a dataset with too many variables is difficult. Learn how to reduce the number of variables in your data using principal component analysis. Not only does this help to get a better understanding of your data. PCA also enables you to condense information to single indices and to solve multicollinearity problems in a regression analysis with many intercorrelated variables.

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For Business

GroupTraining 2 or more people?

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In the following Tracks

Marketing Analytics with R

Go To Track

Datasets

Churn dataSales dataSales data, months 2-4Survival dataDefault dataNews dataFirst CLV datasetSecond CLV datasetCustomer data

Collaborators

Collaborator's avatar
Chester Ismay
Collaborator's avatar
Nick Solomon
Verena Pflieger HeadshotVerena Pflieger

Data Scientist at INWT Statistics

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