Retail analytics using MS Excel - Covering Forecasting, Market Basket, RFM, Customer Valuation & Price Bundling
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What you'll learn
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Become proficient in using powerful tools such as excel solver to create
forecasting models
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Learn how to estimate the trend and seasonal aspects of sales
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Perform market basket analysis and calculate lift to derive a store layout
that maximizes sales from complementary products
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Understand how to interpret the result of Linear Regression model and
translate them into actionable insight
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Learn practical concepts of how to get revenue/profit optimized price point
in case of Bundle products.
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Learn why cable companies bundle landlines, cell phone service, TV service,
and Internet service (Bundling)
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Perform RFM (Recency, frequency, and monetary value) analysis to help you
maximize profit from promotional mail campaigns.
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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
Requirements
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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
Description
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
Our Promise
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!
Cheers
Start-Tech Academy
Who this course is for:
Anyone curious to learn the analytics behind most popular marketing
startegies