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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

Determining a product’s relevant attributes

As mentioned before, we will perform a conjoint analysis to weigh the importance that a group of users gives to a given characteristic of a product or service. To achieve this, we will perform a multivariate analysis to determine the optimal product concept. By evaluating the entire product (overall utility value), it is possible to calculate the degree of influence on the purchase of individual elements (partial utility value). For example, when a user purchases a PC, it is possible to determine which factors affect this and how much (important). The same method can be scaled to include many more features.

The data to be used is in the form of different combinations of notebook features in terms of RAM, storage, and price. Different users ranked these combinations.

We will use the following Python modules in the next example:

  • Pandas: Python package for data analysis and data manipulation.
  • NumPy: Python package that...
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