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Introduction to R for Business Intelligence

You're reading from   Introduction to R for Business Intelligence Profit optimization using data mining, data analysis, and Business Intelligence

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Product type Paperback
Published in Aug 2016
Publisher Packt
ISBN-13 9781785280252
Length 228 pages
Edition 1st Edition
Languages
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Author (1):
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Jay Gendron Jay Gendron
Author Profile Icon Jay Gendron
Jay Gendron
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Table of Contents (13) Chapters Close

Preface 1. Extract, Transform, and Load FREE CHAPTER 2. Data Cleaning 3. Exploratory Data Analysis 4. Linear Regression for Business 5. Data Mining with Cluster Analysis 6. Time Series Analysis 7. Visualizing the Datas Story 8. Web Dashboards with Shiny A. References
B. Other Helpful R Functions C. R Packages Used in the Book
D. R Code for Supporting Market Segment Business Case Calculations

Creating a marketing-campaign Shiny app


The book has developed examples of analysis projects for Bike Sharing LLC. Now you will extend one of these by building a second Shiny App. In Chapter 5, Data Mining with Cluster Analysis, you spent time researching targeted customer marketing segments to help the marketing group identify clusters of customers and drive more effective marketing campaigns. Imagine that marketing wants the ability to interact with the analysis and explore differing numbers of clusters. They would also like to generate lists of customers who fit a particular profile so that they can act on potential campaigns more quickly.

Note

The following examples provide a sense of developing a more realistic and useful Shiny app. The code snippets do not generate a complete web app, but rather focus on the added core functionality.

We highly recommend that you use the complete code for the marketing campaign app by navigating to the Ch8-CampaignCreatorApp repository folder. Follow...

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