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Diploma in Marketing Analytics
Learn how to use different techniques in marketing analytics and market mix models in this free online course.
Description
Diploma in Marketing Analytics is a free online course that offers a comprehensive guide to understanding the functions of different marketing mix models. This course will teach you how to use R programming, do social network analysis, and master other models for effective marketing analysis. It begins with a breakdown of consumers' wants and R programming, and how it can be used to solve real-life problems in marketing analytics.
Next, you will learn about customer segmentation and targeting positioning, along with geographical segmentation. You will also study demand focusing, pricing and major predictors of sales in marketing analytics. Then you will discuss the advertising models and how to use macro-level cost analysis in marketing mix models. Analyze situations where market decisions affect customers and study the recommendation engines and retail analytics in the marketing process. Finally, look into filtering and the features of collaborative filtering in marketing analytics.
This free online course provides practical knowledge and numerous applications of recency, frequency, monetary (RFM) value; market basket analysis; interactive dashboard creation as well as the customer-churn approach to ensure a great learning experience throughout. It will be of significant value to anyone interested in harnessing marketing analytics for personal or professional use. Start your next learning journey by registering for this course and upgrade your marketing analytics skills.
Start Course NowModules
Introduction to R Programming
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Introduction to R Programming - Learning Outcomes
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Understanding R programming and Installation
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Functions and their Syntax
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Matrix and Data Frame
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Data Manipulation
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Handling Basic Data Analytics
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Creating a Bar Plot
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Introduction to R Programming - Lesson Summary
Consumers Wants
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Consumers Wants - Learning Outcomes
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Wants, Needs and Demands in Marketing
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Conjoint Analysis in Consumers Wants
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Rating-Based of Conjoint Analysis
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Pricing in Conjoint Analysis
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Choice Modeling Method
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Choice Based Conjoint
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Consumer Wants - Lesson Summary
Segmentation, Targeting and Positioning
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Segmentation, Targeting and Positioning - Learning Outcomes
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Segmentation, Targeting and Positioning Methodology
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Segmentation, Targeting and Positioning Concepts
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Steps in Segmentation, Targeting and Positioning
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Solving a Problem with Clustering Methods
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Application of Multiple Techniques
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Segmentation, Targeting and Positioning - Lesson Summary
Demand Focusing and Pricing
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Demand Focusing and Pricing - Learning Outcomes
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Demand and Sales Forecasting
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Bundle Pricing
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Using Analytics to Forecast a Demand
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Technology Adoption Model
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Demand Focusing and Pricing - Lesson Summary
Understanding Pricing
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Understanding Pricing - Learning Outcomes
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Pricing and Skimming
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Power Block Pricing
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Solving Pricing Problems
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Price Base Segmentation
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Understanding Pricing - Lesson Summary
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Markdown Pricing and Dynamic Pricing
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Price Bundling
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Price Sales Promotion
Marketing Mix Models and Advertising Model
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Marketing Mix Models and Advertising Models - Learning Outcomes
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Micro Level Analysis
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Linear Model
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Impact of the Advertising Model
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Advertising Models Equation
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Media Data
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Marketing Mix Models and Advertising Models - Lesson Summary
Diploma in Marketing Analytics - First Assessment
Recommendation Engine and Retail Analysis
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Recommendation Engine and Retail Analysis - Learning Outcomes
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Recommendation Engine
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Collaborative Filtering
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Hands-On Item Collaborative Filtering
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User Collaborative Filtering
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Application of Recommendation Engine
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Working with Sparse Datasets
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Recommendation Engine and Retail Analysis - Lesson Summary
RFM and Market Basket Analysis
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RFM and Market Basket Analysis - Learning Outcomes
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Recency Frequency Monetary Technique
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Recency Frequency Monetary Analysis in R
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Market Basket Analysis
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Data Mining Technique
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Market Basket Analysis Hands-On
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RFM and Market Basket Analysis - Lesson Summary
Customers Churn and Customer Service Value
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Customers Churn and Customer Service Value - Learning Outcomes
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Customer Churn Prediction
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Customer Churn Control
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Customer Switching Behavior
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Customer Lifetime Value
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Customer Lifetime Value in Specific Cases
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Survival Analysis in Customer Churn
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Customers Churn and Customer Service Value - Lesson Summary
Text Mining and Sentiment Analytics
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Text Mining and Sentiment Analytics - Learning Outcomes
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Text Mining Application
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Understanding Tokenization
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Text Mining in Marketing
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Spam Detection
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R Programming in Naive Bayes Algorithm
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Text Mining and Sentiment Analytics - Lesson Summary
Sentiment Analytics
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Sentiment Analytics - Lesson Summary
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Sentiment Analytics - Learning Outcomes
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Naïve Bayes Algorithm in Sentiment Mining
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Algorithms for Sentiment Analysis
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Sentiment Mining and Text Mining
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Topic Modeling in Sentiment Analysis
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Sentiment and Emotion Mining Approach
Social Network Analysis and Excel Dashboard
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Social Network Analysis and Excel Dashboard - Learning Outcomes
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Social Network Analysis for Marketing Management
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Manufacturing Company Case Study in Marketing
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Solving a Case with Social Network Analysis
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Social Network Analysis in Real Life Situation
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Creating an Interactive Dashboard
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Creating a Dashboard from a Dataset
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Social Network Analysis and Excel Dashboard - Lesson Summary
Diploma in Marketing Analytics - Second Assessment
Course assessment
Learning Outcomes
Upon completion of this course, you should be able to:
- Identify the influence of key marketing concepts in marketing analytics
- Explain the utilization of R programming in marketing analytics
- Analyze the concept of customer segmentation and target positioning
- Identify the marketing mix models in analytics
- Explain the recommendation engine and retail analytics
- Describe the importance of the customer-churn approach in marketing analytics
- Analyze the applications of text mining in marketing analytics
- Explain the concept of sentiment analytics and the use of Naive Bayes classifiers for sentiment mining
- Identify social network analysis to create connections between people and their business decisions
Certification
All Alison courses are free to enrol, study and complete. To successfully complete this Diploma course and become an Alison Graduate, you need to achieve 80% or higher in each course assessment. Once you have completed this Diploma course, you have the option to acquire an official Diploma, which is a great way to share your achievement with the world. Your Alison Diploma is:
Ideal for sharing with potential employers - include it in your CV, professional social media profiles and job applications
An indication of your commitment to continuously learn, upskill and achieve high results
An incentive for you to continue empowering yourself through lifelong learning
Alison offers 3 types of Diplomas for completed Diploma courses:
Digital Diploma - a downloadable Diploma in PDF format, immediately available to you when you complete your purchase
Diploma - a physical version of your officially branded and security-marked Diploma, posted to you with FREE shipping
Framed Diploma - a physical version of your officially branded and security-marked Diploma in a stylish frame, posted to you with FREE shipping
All Diplomas are available to purchase through the Alison Shop. For more information on purchasing Alison Diplomas, please visit our FAQs. If you decide not to purchase your Alison Diploma, you can still demonstrate your achievement by sharing your Learner Record or Learner Achievement Verification, both of which are accessible from your Dashboard. For more details on our Diploma pricing, please visit our Pricing Page.
