MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.34 GB | Duration: 3h 4m
Master data analytics and explore marketing, social media, predictive, and prescriptive analytics.
What you'll 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.
A basic understanding of data analytics is beneficial.
**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: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:3 hours of video tutorials20 individual video lecturesExercise files to follow alongCertificate of completion
Section 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
Section 2: Social Media Analytics
Lecture 15 Social Media Analytics
Lecture 16 Sentiment Analysis: Part 1
Lecture 17 Sentiment Analysis: Part 2
Section 3: Predictive and Prescriptive Analytics
Lecture 18 Predictive Analytics
Lecture 19 Prescriptive Analytics: Part 1
Lecture 20 Prescriptive Analytics: Part 2
Section 4: Exercise and Conclusion
Lecture 21 Exercise One
Lecture 22 Exercise Two
Lecture 23 Conclusion
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.
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