Marketing Analytics and Retail Business Management
Retail analytics using MS Excel – Covering Forecasting, Market Basket, RFM, Customer Valuation & Price Bundling
Note: 4.5/5 (1,078 notes) 98,308 students
Instructor(s): Start-Tech Academy
Last update: 2022-08-17
What you’ll learn
- Become proficient in using powerful tools such as excel solver to create forecasting models
- Learn how to estimate the trend and seasonal aspects of sales
- Perform market basket analysis and calculate lift to derive a store layout that maximizes sales from complementary products
- Understand how to interpret the result of Linear Regression model and translate them into actionable insight
- Learn practical concepts of how to get revenue/profit optimized price point in case of Bundle products.
- Learn why cable companies bundle landlines, cell phone service, TV service, and Internet service (Bundling)
- Perform RFM (Recency, frequency, and monetary value) analysis to help you maximize profit from promotional mail campaigns.
- Learn to calculate customer’s lifetime value under different scenarios and use it to increase the company’s profitability.
- Incorporate the impact of discount rate and retention rate to calculate customer value
- You will need a PC with any version of Excel installed in it
- Basic understanding of Excel operations like opening, closing and saving a file
You’re looking for a complete course on understanding Marketing Analytics and Retail Business Management to drive business decisions involving production schedules, inventory management, promotional mail optimization, store layouting, estimating right bundle price, customer valuation and many other parts of the business., right?
You’ve found the right Marketing Analytics & Retail Business Management course! This course teaches you everything you need to know about different forecasting models, Market Basket analysis, conducting market research, marketing analytics, RFM (recency, frequency, monetary) analysis, Customer Valuation methods & Price Bundling analysis and how to implement these models in Excel using advanced excel tool.
After completing this course you will be able to:
Implement forecasting models such as simple linear, simple multiple regression, Additive and multiplicative trend and seasonality model and many more, required for devising marketing analytics strategies effectively.
Perform marketing analytics and market basket analysis and calculate lift to derive a store layout that maximizes sales from complementary products.
Do RFM (Recency, frequency, and monetary value) analysis to help you maximize profit from promotional mail campaigns.
Increase revenue/profit of your firm by implementing revenue / profit maximizing bundle price point using marketing analytics tool like Excel solver Add-in
Understand the value of your customers to make intelligent decisions based on recommendations of marketing analytics and marketing research on how to spend money acquiring them
Confidently practice, discuss and understand different marketing analytics models used by organizations
How this course will help you?
A Verifiable Certificate of Completion is presented to all students who undertake this Marketing Analytics & Retail Business Management course.
If you are a business manager or an executive, or a student who wants to learn and apply forecasting models, marketing analytics techniques based on marketing research in real world problems of business, this course will give you a solid base for that by teaching you the most popular forecasting models and marketing analytics strategies and how to implement them.
Why should you choose this course?
We believe in teaching by example. This course is no exception. Every Section’s primary focus is to teach you the concepts of marketing analytics, marketing research through how-to examples. Each section has the following components:
Theoretical concepts and cases of different forecasting models and marketing analytics techniques
Step-by-step instructions on implementing forecasting models and marketing analytics in excel
Downloadable Excel file containing data and solutions used in each lecture on marketing analytics and retail business management
Class notes and assignments to revise and practice the concepts on marketing analytics and retail business management
The practical classes where we create the model for each of these strategies is something which differentiates this course from any other course available online.
What makes us qualified to teach you?
The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Analytics and we have used our experience to include the practical aspects of Marketing analytics, marketing research, forecasting techniques and data analytics in this course.
We are also the creators of some of the most popular online courses – with over 170,000 enrollments and thousands of 5-star reviews like these ones:
This is very good, i love the fact the all explanation given can be understood by a layman – Joshua
Thank you Author for this wonderful course. You are the best and this course is worth any price. – Daisy
Teaching our students is our job and we are committed to it. If you have any questions about the course content, marketing analytics, marketing research, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.
Download Practice files, take Quizzes, and complete Assignments
With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts on Marketing analytics, marketing research, forecasting techniques. Each section contains a practice assignment for you to practically implement your learning on Marketing analytics, marketing research, forecasting techniques.
What is covered in this course?
Understanding how future sales will change is one of the key information needed by manager to take data driven decisions. In this course, we will explore how one can use marketing analytics tools and forecasting models to
See patterns in time series data
Make forecasts based on models
Let me give you a brief overview of the course
Section 1 – Introduction
In this section we will learn about the course structure containing Marketing analytics, marketing research, forecasting techniques.
Section 2 – Basics of Forecasting
In this section, we will discuss about the basic of forecasting and we will also learn the easiest way to create simple linear regression model in Excel
Section 3 – Getting Data Ready for Regression Model
In this section you will learn what actions you need to take step by step to get the data and then prepare it for the marketing analytics purpose. These steps are very important.
We start with understanding the importance of business knowledge then we will see how to do data exploration. We learn how to do uni-variate analysis and bi-variate analysis then we cover topics like outlier treatment and missing value imputation. These are the building blocks of implementing marketing analytics techniques effectively.
Section 4 – Forecasting using Regression Model
This section starts with simple linear regression and then covers multiple linear regression. We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don’t understand it, it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures.
We also look at how to quantify models accuracy, what is the meaning of F statistic, how categorical variables in the independent variables data set are interpreted in the results.
Section 5 – Handling Special events like Holiday sales
In this section we will learn how to incorporate effects of Day of Week Effect, Month Effect or any special event such Holidays, pay day etc.
Section 6 – Identifying Seasonality & Trend for Forecasting
In this section we will learn about trends and seasonality and how to use the Solver to develop an additive or multiplicative model to estimate trends and seasonality. We will also learn how to use moving averages to eliminate seasonality to easily see trends in sales.
Section 7 – Market Basket Analysis and Lift
In this section we will learn about Marketing analytics, marketing research, market basket analysis and learn how to calculate lift to derive a store layout that maximizes sales from complementary products.
Section 8 – Recency, frequency, and monetary value analysis
In this section we will learn techniques to perform RFM (Recency, frequency, and monetary value) analysis to help you maximize profit from promotional mail campaigns.
Section 9 – Recency, frequency, and monetary value analysis
In this section we will learn price bundling techniques and learn how to increase revenue/profit of your firm by implementing revenue / profit maximizing price point using Excel solver Add-in
Section 10 – Recency, frequency, and monetary value analysis
In this section, we will discuss about the basic of concepts of Customer Lifetime value and learn how to create excel model to find lifetime customer value and perform sensitivity analysis to capture variations in lifetime value under different scenarios.
Section 11 – Excel crash course
If you’re new to Excel, or you’ve played around with it but want to get more comfortable with Excel’s advanced features required for this course. Either way, this section will be great for you to revise your rusty excel skills .
Some of the examples in this course are from the book Marketing Analytics: Data-Driven Techniques with Microsoft Excel [Winston, Wayne L.]. We suggest this book as reading material for anyone aspiring to be a marketing analyst and gaining knowledge on Marketing analytics, marketing research, forecasting techniques and data analytics.
I am pretty confident that the course will give you the necessary knowledge and skills related to Marketing analytics, marketing research, forecasting techniques, to immediately see practical benefits in your workplace.
Go ahead and click the enroll button, and I’ll see you in lesson 1 of this Marketing Analytics course!
Who this course is for
- Anyone curious to learn the analytics behind most popular marketing startegies
- Course Introduction
- Course resources
- Part 1: Forecasting
- Basics of Forecasting
- This is a milestone!
- Creating Linear Model with Trendlines
- 1.1 Getting Data ready for Regression Model
- Gathering Business Knowledge
- Data Exploration
- The Data and the Data Dictionary
- Univariate analysis and EDD
- Descriptive Data Analytics or EDD in Excel
- Outlier Treatment
- Outlier treatment in Excel
- Missing Value Imputation
- Missing value imputation in Excel
- Variable Transformation in Excel
- Dummy variable creation: Handling qualitative data
- Dummy Variable Creation in Excel
- Correlation Analysis
- Creating Correlation Matrix in Excel
- 1.2 Forecasting using Regression Model
- The Problem Statement
- Regression model – Presentations
- Basic Equations and Ordinary Least Squares (OLS) method
- Assessing accuracy of predicted coefficients
- Assessing Model Accuracy: RSE and R squared
- Creating Simple Linear Regression model
- Multiple Linear Regression
- The F – statistic
- Interpreting results of Categorical variables
- Creating Multiple Linear Regression model
- 1.3 Handling Special events like Holiday sales
- Forecasting in presence of special events
- Excel: Running Linear Regression using Solver
- Excel: Including the impact of Special Events
- 1.4 Identifying Seasonality & Trend for Forecasting
- Models to identify Trend & Seasonality
- Excel: Additive model to identify Trend & Seasonality
- Excel: Multiplicative model to identify Trend & Seasonality
- Market Basket Analysis
- Market Basket and Lift – Introduction
- Named Ranges – Excel
- Indirect Function – Excel
- 2-way lift calculation in Excel
- 2-way lift calculation – Dynamic
- 2-way lift data table creation
- 3-way lift calculation
- Store Layout optimization using Lift values
- RFM (recency, frequency, monetary) Analysis
- RFM (recency, frequency, monetary) Analysis
- RFM Analysis in Excel- Part 1
- RFM Analysis in Excel- Part 2
- Part 2: Pricing
- Steps of setting a Pricing policy
- Different Pricing Objectives
- 2.1 Estimating Demand
- Estimating Demand
- Forms of Demand Curve
- Price Elasticity Examples
- Excel: Estimating Linear Demand Curve
- Excel: Estimating Power Demand curve with Elasticity
- Excel: Estimating Power Demand Curve with points
- Subjective Demand curve
- Excel: Estimating Subjective Demand Curve
- 2.3 Evaluating Pricing Strategies
- Price Bundling
- Types of Bundling
- The Bundling Problem
- Excel: Solving Bundling problem Part 1
- Excel: Solving Bundling problem Part 2
- Excel: Solving Bundling problem (Price Reversal)
- Non-Linear Pricing Strategies
- 3.1 Lifetime Customer Value
- Lifetime Customer Value – Key concepts
- Lifetime Customer Value – Excel model
- 3.2 Variations and Sensitivity Analysis
- Sensitivity Analysis in Excel
- Variations in finding customer value
- Appendix 1: Excel crash course
- Worksheet Basics
- Entering values and Formulas
- Data Formats
- Data Handling Basics – Cut, Copy and Paste
- Saving and Printing – Basics
- Basic Formula Operations
- Mathematical Formulas
- Textual Formulas
- Logical Formulas
- Date-Time Formulas
- Lookup Formulas ( V Lookup, Hlookup, Index-Match )
- Data Tools
- Formatting data and tables
- Pivot Tables
- Advance Excel- Solver, Data tables
- Popular Excel charts
- Congratulations & about your certificate
- The final milestone!
- Bonus Lecture
Time remaining or 942 enrolls left
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