Data Analytics for Marketing: A practical guide to analyzing marketing data using Python
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Turn data into useful information and make data-driven decisions to enhance marketing strategies.
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What Stands Out
Product Details
| Publisher | Packt Publishing |
| Publication date | May 10, 2024 |
| Language | English |
| Print length | 452 pages |
| ISBN-10 | 1803241608 |
| ISBN-13 | 978-1803241609 |
| Item Weight | 1.7 pounds (770 grams) |
| Dimensions | 7.5 x 1.02 x 9.25 inches (19.1 x 2.6 x 23.5 cm) |
Who Should Buy?
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Marketing Professionals
Ideal for marketers seeking to leverage data analytics to enhance their campaigns and ROI through actionable insights.
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Data Analysts
Perfect for data analysts wanting to expand their skills in Python for more effective analysis of marketing data.
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Students and Learners
Great for students in marketing or data science, providing practical applications of theoretical knowledge in real-world scenarios.
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Beginners in Python
Not suitable for absolute beginners, as it may require prior knowledge of Python programming for effective comprehension.
Product Description
Data Analytics for Marketing: A practical guide to analyzing marketing data using Python
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Marketing Editorial Review
Data Analytics for Marketing: A practical guide to analyzing marketing data using Python is a comprehensive resource published by Packt Publishing, crafted to help marketers effectively analyze their marketing data. The book spans 452 pages and is presented in English, making it accessible to a wide audience. With the latest publication date of May 10, 2024, this guide offers up-to-date methodologies and practical approaches that embrace Python's capabilities in data analysis. Readers can expect to delve into various analytical techniques tailored for marketing, crucial for making informed decisions based on data-driven insights.
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Pros
- Comprehensive coverage of data analysis techniques
- Practical examples using Python
- Up-to-date methodologies for marketers
- Accessible for beginners and professionals
- Well-structured and easy to follow
Cons
- Lacks advanced topics for seasoned analysts
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Features & Benefits
- Learn to analyze marketing data using effective statistical techniques.
- Understand customer preferences to boost marketing strategies.
- Implement Python libraries like DoWhy, Pandas, and Prophet effectively.
- Gain insights through causal inference and data modeling.
- Visualize and present large data in an understandable way.
- Improve decision-making with robust customer analytics.
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