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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

Summary

In this chapter, we have dived into the details of sales analysis and markdown applications. As discussed, there is a trade-off between reducing the price of items to increase sales and reduce stock-related costs and the amount of revenue that is lost due to that decrease in price. In the case of retail, these outcomes are impacted by multiple factors, among which are the location of a given store, the environmental and economic conditions, and seasonality, as we saw with the analysis of sales during different holiday seasons.

The analysis and prediction of sales and markdowns can be applied to fine-tune the price reductions applied to maintain the equilibrium between profitability and sales, as well as to have a deep understanding of the variables involved and their relative impact that can lead to the design of better markdown strategies.

In the next chapter, we will dive into the specifics of learning the consumer behavior at e-commerce retailers, understanding consumer...

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