Analytical Methods for Effective Data Analysis
Analytical Methods for Effective Data Analysis, available at $19.99, has an average rating of 4.31, with 23 lectures, 3 quizzes, based on 27 reviews, and has 263 subscribers.
You will learn about Analyze customer data using segmentation models for targeted marketing campaigns. Implement Recency Frequency Monetary (RFM) models to optimize customer engagement. Evaluate the success of social media campaigns by measuring brand mentions and sentiment. Apply predictive analytics techniques to make informed predictions about future events. Utilize prescriptive analytics to develop strategies for achieving specific business goals. Create revenue optimization models to optimize profit through data-driven decisions. Demonstrate an understanding of dynamic pricing and its role in revenue management. Develop practical skills in setting up and utilizing sentiment analysis for text data. This course is ideal for individuals who are People who want to learn data analytics and different analytical methods. or Those who want to understand marketing, social media, predictive, and prescriptive analytics. or Marketing professionals, business analysts, or anyone interested in harnessing the power of data. It is particularly useful for People who want to learn data analytics and different analytical methods. or Those who want to understand marketing, social media, predictive, and prescriptive analytics. or Marketing professionals, business analysts, or anyone interested in harnessing the power of data.
Enroll now: Analytical Methods for Effective Data Analysis
Summary
Title: Analytical Methods for Effective Data Analysis
Price: $19.99
Average Rating: 4.31
Number of Lectures: 23
Number of Quizzes: 3
Number of Published Lectures: 23
Number of Published Quizzes: 3
Number of Curriculum Items: 26
Number of Published Curriculum Objects: 26
Original Price: $89.99
Quality Status: approved
Status: Live
What You Will Learn
- Analyze customer data using segmentation models for targeted marketing campaigns.
- Implement Recency Frequency Monetary (RFM) models to optimize customer engagement.
- Evaluate the success of social media campaigns by measuring brand mentions and sentiment.
- Apply predictive analytics techniques to make informed predictions about future events.
- Utilize prescriptive analytics to develop strategies for achieving specific business goals.
- Create revenue optimization models to optimize profit through data-driven decisions.
- Demonstrate an understanding of dynamic pricing and its role in revenue management.
- Develop practical skills in setting up and utilizing sentiment analysis for text data.
Who Should Attend
- People who want to learn data analytics and different analytical methods.
- Those who want to understand marketing, social media, predictive, and prescriptive analytics.
- Marketing professionals, business analysts, or anyone interested in harnessing the power of data.
Target Audiences
- People who want to learn data analytics and different analytical methods.
- Those who want to understand marketing, social media, predictive, and prescriptive analytics.
- Marketing professionals, business analysts, or anyone interested in harnessing the power of data.
**This course includes downloadable exercise files to work with**
Welcome to Analytical Methods for Effective Data Analysis. This course is designed to provide you with a comprehensive understanding of data analytics by breaking it down into four main components: marketing analytics, social media analytics, predictive analytics, and prescriptive analytics.
In this course, you will learn how these different types of analytics fit together seamlessly. We’ll start by exploring the customer-centric world of marketing analytics, covering topics such as customer life cycles and various marketing models, including customer segmentation, acquisition, RFM, market basket analysis, and more. You’ll discover how these models can help retain and engage customers effectively.
Moving on, we will dive into social media analytics, where you’ll gain insights into measuring, collecting, and analyzing data from social media platforms. You’ll also explore sentiment analysis, a crucial tool for understanding public opinions and sentiments expressed in textual content.
The course’s third section focuses on predictive analytics, using statistics, machine learning, and data mining to predict future events. Additionally, we’ll delve into prescriptive analytics, which guides decision-making by optimizing key metrics based on past performance and trends.
By the end of this course, you will possess the skills and knowledge needed to excel in the world of data analytics. Whether you’re a marketing professional, business analyst, or anyone interested in harnessing the power of data, this course will help equip you with practical tools and insights to make informed decisions and drive success in your field. Don’t miss this opportunity to master analytical methods for effective data analysis.
In this course, students will learn how to:
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Analyze customer data using segmentation models for targeted marketing campaigns.
-
Implement Recency Frequency Monetary (RFM) models to optimize customer engagement.
-
Evaluate the success of social media campaigns by measuring brand mentions and sentiment.
-
Apply predictive analytics techniques to make informed predictions about future events.
-
Utilize prescriptive analytics to develop strategies for achieving specific business goals.
-
Create revenue optimization models to optimize profit through data-driven decisions.
-
Demonstrate an understanding of dynamic pricing and its role in revenue management.
-
Develop practical skills in setting up and utilizing sentiment analysis for text data.
This course includes:
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3 hours of video tutorials
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20 individual video lectures
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Exercise filesto follow along
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Certificate of completion
Course Curriculum
Chapter 1: Analytics Beginnings and Marketing Analytics
Lecture 1: Introduction
Lecture 2: WATCH ME: Essential Information for a Successful Training Experience
Lecture 3: DOWNLOAD ME: Course Exercise File
Lecture 4: Downloadable Course Transcript
Lecture 5: Four Types of Analytics
Lecture 6: Customer Life Cycle: Part 1
Lecture 7: Customer Life Cycle: Part 2
Lecture 8: Marketing Model Types: Part 1
Lecture 9: Marketing Model Types: Part 2
Lecture 10: Marketing Model Types: Part 3
Lecture 11: Marketing Model Types: Part 4
Lecture 12: Marketing Model Types: Part 5
Lecture 13: Marketing Model Types: Part 6
Lecture 14: Marketing Model Types: Part 7
Chapter 2: Social Media Analytics
Lecture 1: Social Media Analytics
Lecture 2: Sentiment Analysis: Part 1
Lecture 3: Sentiment Analysis: Part 2
Chapter 3: Predictive and Prescriptive Analytics
Lecture 1: Predictive Analytics
Lecture 2: Prescriptive Analytics: Part 1
Lecture 3: Prescriptive Analytics: Part 2
Chapter 4: Exercise and Conclusion
Lecture 1: Exercise One
Lecture 2: Exercise Two
Lecture 3: Conclusion
Instructors
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Simon Sez IT
870,000+ Students, 260+ Courses, Learners in 180+ Countries
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 1 votes
- 3 stars: 7 votes
- 4 stars: 6 votes
- 5 stars: 13 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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