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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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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

Understanding customer segmentation

Customer segmentation is the practice of classifying customers into groups based on shared traits so that businesses may effectively and appropriately market to each group. In business-to-business (B2B) marketing, a firm may divide its clientele into several groups based on a variety of criteria, such as location, industry, the number of employees, and previous purchases of the company’s goods.

Businesses frequently divide their clientele into segments based on demographics such as age, gender, marital status, location (urban, suburban, or rural), and life stage (single, married, divorced, empty nester, retired). Customer segmentation calls for a business to collect data about its customers, evaluate it, and look for trends that may be utilized to establish segments.

Job title, location, and products purchased—for example—are some of the details that can be learned from purchasing data to help businesses to learn about...

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