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The Art of Data-Driven Business

You're reading from   The Art of Data-Driven Business Transform your organization into a data-driven one with the power of Python machine learning

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781804611036
Length 314 pages
Edition 1st Edition
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Author (1):
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Alan Bernardo Palacio Alan Bernardo Palacio
Author Profile Icon Alan Bernardo Palacio
Alan Bernardo Palacio
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Data Analytics and Forecasting with Python
2. Chapter 1: Analyzing and Visualizing Data with Python FREE CHAPTER 3. Chapter 2: Using Machine Learning in Business Operations 4. Part 2: Market and Customer Insights
5. Chapter 3: Finding Business Opportunities with Market Insights 6. Chapter 4: Understanding Customer Preferences with Conjoint Analysis 7. Chapter 5: Selecting the Optimal Price with Price Demand Elasticity 8. Chapter 6: Product Recommendation 9. Part 3: Operation and Pricing Optimization
10. Chapter 7: Predicting Customer Churn 11. Chapter 8: Grouping Users with Customer Segmentation 12. Chapter 9: Using Historical Markdown Data to Predict Sales 13. Chapter 10: Web Analytics Optimization 14. Chapter 11: Creating a Data-Driven Culture in Business 15. Index 16. Other Books You May Enjoy

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

advanced analytics

using, in business 4

Akaike’s Information Criteria (AIC) 92

analysis of variance (ANOVA) 26, 27

Apriori algorithm

used, for performing market basket analysis 143-148

used, for product bundling 142, 143

B

Bayesian Information Criteria (BIC) 92

binary logistic regression 95

business operations

improving, with web analytics 235

business-to-business (B2B) 176

C

causality 32

causation 32-37

choice-based conjoint 81

churn 154

client segments

creating 190-196

clustering 41, 42, 193

clusters

as customer segments 196-206

conjoint analysis 80, 81

conjoint studies 80

uses 80

conjoint experiment

designing 82, 83

correlation 29

correlation heatmap 32

correlation matrix 29-31

corr method...

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