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Start-Tech Academy

You're looking for a complete course on understanding Forecasting models and forecasting analytics to drive business decisions involving production schedules, inventory management, manpower planning, demand forecasting, and many other parts of the business., right?

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You're looking for a complete course on understanding Forecasting models and forecasting analytics to drive business decisions involving production schedules, inventory management, manpower planning, demand forecasting, and many other parts of the business., right?

You've found the right Marketing Analytics: Forecasting Models with Excel. This course teaches you everything you need to know about different forecasting models and how to implement these models for devising forecasting analytics in Excel using advanced excel tool.

After completing this course you will be able to:

  • Implement forecasting analytics and forecasting models such as simple linear, simple multiple regression, Ratio to Moving Average, Winter's method for exponential smoothing with trend and seasonality, famous Bass diffusion model and many more.

  • Increase revenue/profit of your firm by implementing accurate forecasting analytics using Excel solver Add-in

  • Confidently practice, discuss and understand different Forecasting analytics strategies and forecasting models used by organizations

  • Creating demand forecasting strategies using forecasting analytics techniques and various forecasting models.

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this Marketing Analytics: Forecasting Models with Excel course.

If you are a business manager or an executive, or a student who wants to learn and apply forecasting analytics and forecasting models in real world problems of business, this course will give you a solid base by teaching you the most popular forecasting models and how to implement it for effective demand forecasting and for devising forecasting analytics techniques.

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 on forecasting analytics, demand forecasting, forecasting models through how-to examples. Each section has the following components:

  • Theoretical concepts and use cases of different forecasting models and forecasting analytics techniques

  • Step-by-step instructions on implement forecasting models and forecasting analytics techniques in excel for demand forecasting

  • Downloadable Excel file containing data and solutions used in each lecture on forecasting models and forecasting analytics

  • Class notes and assignments to revise and practice the concepts on demand forecasting, forecasting models and forecasting analytics techniques

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 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, 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. Each section contains a practice assignment for you to practically implement your learning.

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 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

  • 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 a step by step to get the data and then prepare it for the analysis 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.

  • 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 dataset 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 - Handling Changing Trend & Seasonality over time

In this section we will learn about Winter’s Method that changes trend and seasonal index estimates during each period has a better chance of keeping up with changes than other methods.

  • Section 8 - Forecasting models for New Products

In this section we will learn techniques to forecast new product sales. It is difficult to forecast when we have little or no historical data. The S curve can be used when we have little data and the famous bass diffusion model can be used to predict product sales even before the product is launched in the market.

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.

I am pretty confident that the course will give you the necessary knowledge and skills related to forecasting analytics, forecasting models and demand forecasting strategies; to immediately see practical benefits in your work place.

Go ahead and click the enroll button, and I'll see you in lesson 1 of this course on forecasting analytics and forecasting models.

Cheers

Start-Tech Academy

Enroll now

What's inside

Learning objectives

  • Become proficient in using powerful tools such as excel solver to create forecasting models
  • Learn about two of the most used forecasting tools: simple linear and simple multiple regression
  • Learn how to estimate the trend and seasonal aspects of sales
  • Learn to generate forecasts using the ratio to moving average forecasting method
  • Forecast using dynamic trend and seasonal index using winter's method
  • Learn forecasting for new product launch with little or no history about sales of a product
  • Learn how to use s curves to forecast sales of a new product
  • Learn how to forecast product sales even before the product comes to market using popular the bass diffusion model
  • Indepth knowledge of data collection and data preprocessing for linear regression problem
  • Understand how to interpret the result of linear regression model and translate them into actionable insight

Syllabus

Introduction
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
Read more
Basics of Forecasting
Course Resources
This is a milestone!
Creating Linear Model with Trendlines
In this section you will learn what actions you need to take a step by step to get the data and then prepare it for the analysis these steps are very important. We start with understanding the import
Gathering Business Knowledge
Data Exploration
The Data and the Data Dictionary
Univariate analysis and EDD
Discriptive Data Analytics in Excel
Outlier Treatment
Identifying and Treating Outliers in Excel
Missing Value Imputation
Identifying and Treating missing values in Excel
Variable Transformation in Excel
Dummy variable creation: Handling qualitative data
Dummy Variable Creation in Excel
Correlation Analysis
Creating Correlation Matrix in Excel
Quiz
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
The Problem Statement
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
Assignment 1: Regression based Forecasting
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.
Forecasting in presence of special events
Excel: Running Linear Regression using Solver
Excel: Including the impact of Special Events
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 mo
Models to identify Trend & Seasonality

The example in this lecture is from Marketing Analytics: Data-Driven Techniques with Microsoft Excel [Winston, Wayne L.]

Moving Average Method
Assignment 2: Identifying Trend and Seasonality
In this section we will learn about Winter’s Method that changes trend and seasonal index estimates during each period has a better chance of keeping up with changes than other methods.
Winter's Method to accomodate changing Trend & Seasonality
In this section we will learn techniques to forecast new product sales. It is difficult to forecast when we have little or no historical data. The S curve can be used when we have little data and the
S-curve for New products
Excel: Using Logistic curve to model S-curve
Excel: Using Gompertz curve to model S-curve
Bass Diffusion Model for New Products
Excel: Implementing Bass Diffusion Model
Final Course Quiz
Assignment 3: Bass Model
Appendix 1: Excel crash course
Important Excel Functions - Sum, Average, Concatenate, Trim
Important Excel Functions- Vlookup, If, Count If, Sum if
Sorting, Filtering and Data Validation
Text-to-columns and remove duplicates
Advanced Filter option
Pivot tables
Popular Excel charts
NEW! Analyze Data option in Excel - only for Microsoft 365 users
Bonus Lecture
The final milestone!

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches learners to implement forecasting analytics and forecasting models using Excel solver Add-in
Covers different Forecasting analytics strategies and models used by organizations
Utilizes practical classes to differentiate this course from others available online
Taught by professionals with experience in solving business problems using Analytics
Suitable for business managers, executives, and students interested in applying forecasting analytics in real-world problems
Focuses on teaching concepts through practical examples, rather than just theoretical discussions

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Reviews summary

Excel forecasting course

According to students, this course on marketing analytics is well received. Students largely agree that the course is a good course.
Students say this is a good course.
"Its a good course"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Marketing Analytics: Forecasting Models with Excel with these activities:
Review Basic Statistics
Ensure a solid foundation in statistics to support your learning in this course. Review basic statistical concepts, such as mean, median, standard deviation, and correlation.
Browse courses on Statistics
Show steps
  • Review lecture notes, textbooks, or online resources on basic statistics.
  • Solve practice problems to test your understanding of the concepts.
Read 'Marketing Analytics: Data-Driven Techniques with Microsoft Excel'
Supplement your learning by reading a book that covers forecasting analytics, forecasting models, and demand forecasting strategies. This will provide you with a deeper understanding of the concepts taught in the course.
Show steps
  • Obtain a copy of the book, either physically or digitally.
  • Allocate dedicated time for reading.
  • Take notes and highlight key concepts as you read.
  • Use the book as a reference guide for your forecasting projects.
Follow Excel Tutorials on Forecasting
Enhance your understanding of forecasting concepts and techniques by following guided tutorials that provide step-by-step instructions and practical examples.
Browse courses on Forecasting
Show steps
  • Identify reputable online resources or platforms that offer Excel tutorials on forecasting.
  • Choose a tutorial that aligns with your skill level and learning goals.
  • Follow the instructions and complete the exercises provided in the tutorial.
  • Apply the learned techniques to your own forecasting projects.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Create a Forecasting Dashboard in Excel
Create a visually appealing and interactive dashboard in Excel to track and analyze your forecasts. This will help you monitor the performance of your forecasts and make informed decisions.
Browse courses on Forecasting Models
Show steps
  • Gather the necessary data and prepare it for analysis.
  • Create charts and graphs to visualize the data and forecasts.
  • Add interactive elements, such as slicers and filters, to enable users to explore the data and forecasts.
  • Design the dashboard layout and ensure it is user-friendly.
Practice Forecasting using Past Sales Data
Practice using the forecasting models learned in the course by applying them to real-world sales data. This will help you develop proficiency in using Excel's tools and techniques for forecasting.
Browse courses on Forecasting Models
Show steps
  • Select a product or service for which you have historical sales data.
  • Create a scatter plot of the historical sales data.
  • Fit a simple linear regression model to the data.
  • Use the model to forecast future sales.
  • Evaluate the accuracy of the forecast.
Join a Forecasting Study Group
Connect with other learners in a study group to discuss course concepts, share knowledge, and collaborate on projects. This will enhance your understanding of forecasting and provide support from peers.
Browse courses on Forecasting Models
Show steps
  • Identify or create a study group with other participants in the course.
  • Schedule regular meetings to discuss course material, assignments, and projects.
  • Take turns leading discussions and presenting findings.
  • Provide constructive feedback to each other's work.
Forecast Sales for a New Product Launch
Apply your forecasting skills to a real-world project by forecasting sales for a new product launch. This will challenge you to apply the models and techniques learned in the course to a practical business scenario.
Show steps
  • Identify a new product that is about to be launched or has recently been launched.
  • Gather data on historical sales of similar products or market research data.
  • Select appropriate forecasting models, such as the Bass diffusion model.
  • Develop a forecast for the sales of the new product.
  • Present your forecast to stakeholders and discuss the implications for marketing and sales strategies.
Develop a Forecasting Model for a Business Case
Apply your forecasting knowledge to a real business case by developing a comprehensive forecasting model. This will demonstrate your ability to use forecasting techniques to solve practical business problems.
Browse courses on Forecasting Models
Show steps
  • Identify a business problem that can be addressed through forecasting.
  • Gather and analyze relevant data.
  • Develop and validate a forecasting model.
  • Create a detailed report that documents your findings and recommendations.

Career center

Learners who complete Marketing Analytics: Forecasting Models with Excel will develop knowledge and skills that may be useful to these careers:
Marketing Manager
Marketing Managers lead the planning, development, and execution of marketing campaigns. These campaigns may include product launches, brand awareness initiatives, or lead generation drives. As a Marketing Manager, you will use your knowledge of forecasting models and analytics to develop data-driven marketing strategies.
Market Research Analyst
Market Research Analysts collect, analyze, and interpret market data to help businesses understand their customers and make informed decisions. As a Market Research Analyst, you will use your skills in forecasting models and analytics to identify trends, predict demand, and develop new products and services.
Data Analyst
Data Analysts use their skills in data analysis, statistics, and forecasting to identify trends, predict future outcomes, and develop data-driven recommendations. As a Data Analyst, you will use your knowledge of forecasting models and analytics to help businesses make informed decisions.
Business Analyst
Business Analysts use their skills in data analysis, process improvement, and forecasting to help businesses improve their operations. As a Business Analyst, you will use your knowledge of forecasting models and analytics to identify areas for improvement and develop solutions to business problems.
Financial Analyst
Financial Analysts use their skills in financial modeling, forecasting, and risk assessment to help businesses make informed investment and lending decisions. As a Financial Analyst, you will use your knowledge of forecasting models and analytics to develop financial projections and assess the risks and returns of different investments.
Operations Research Analyst
Operations Research Analysts use their skills in mathematical modeling, optimization, and forecasting to help businesses improve their operations. As an Operations Research Analyst, you will use your knowledge of forecasting models and analytics to develop mathematical models that can be used to optimize business processes.
Management Consultant
Management Consultants use their skills in business analysis, process improvement, and forecasting to help businesses improve their performance. As a Management Consultant, you will use your knowledge of forecasting models and analytics to develop data-driven recommendations that can help businesses achieve their goals.
Product Manager
Product Managers are responsible for the development and launch of new products and services. As a Product Manager, you will use your knowledge of forecasting models and analytics to develop product roadmaps, launch new products, and track product performance.
Brand Manager
Brand Managers are responsible for the development and execution of marketing campaigns for their brands. As a Brand Manager, you will use your knowledge of forecasting models and analytics to develop brand strategies, track brand performance, and measure the effectiveness of marketing campaigns.
Marketing Specialist
Marketing Specialists develop and execute marketing campaigns for their companies. As a Marketing Specialist, you will use your knowledge of forecasting models and analytics to develop marketing strategies, track campaign performance, and measure the effectiveness of marketing campaigns.
Sales Manager
Sales Managers lead sales teams and are responsible for achieving sales targets. As a Sales Manager, you will use your knowledge of forecasting models and analytics to develop sales strategies, track sales performance, and forecast future sales.
Account Manager
Account Managers are responsible for managing relationships with key customers. As an Account Manager, you will use your knowledge of forecasting models and analytics to develop customer relationship management strategies, track customer performance, and forecast future sales.
Business Development Manager
Business Development Managers are responsible for developing new business opportunities for their companies. As a Business Development Manager, you will use your knowledge of forecasting models and analytics to identify new market opportunities, develop business plans, and forecast future revenue.
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are successful with their products or services. As a Customer Success Manager, you will use your knowledge of forecasting models and analytics to track customer success, identify opportunities for improvement, and forecast future customer retention.
Technical Writer
Technical Writers create and maintain technical documentation for software, hardware, and other products. As a Technical Writer, you may use your knowledge of forecasting models and analytics to develop documentation that helps users understand how to use and troubleshoot products.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Marketing Analytics: Forecasting Models with Excel.
Provides a comprehensive overview of marketing analytics, including data collection, data preprocessing, model building, and interpretation. It valuable resource for both students and practitioners who want to learn more about marketing analytics.
Provides a comprehensive overview of forecasting methods, including both traditional and modern techniques. It valuable resource for both students and practitioners who want to learn more about forecasting.
Provides a comprehensive overview of forecasting methods, including both traditional and modern techniques. It valuable resource for both students and practitioners who want to learn more about forecasting.
Provides a comprehensive overview of advanced time series analysis techniques. It valuable resource for both students and practitioners who want to learn more about advanced time series analysis.
Provides a comprehensive overview of time series analysis. It valuable resource for both students and practitioners who want to learn more about time series analysis.
Provides a comprehensive overview of time series analysis, including both traditional and modern techniques. It valuable resource for both students and practitioners who want to learn more about time series analysis.
Provides a comprehensive overview of statistical methods for time series analysis. It valuable resource for both students and practitioners who want to learn more about statistical methods for time series analysis.
Provides a comprehensive overview of machine learning for time series forecasting. It valuable resource for both students and practitioners who want to learn more about machine learning for time series forecasting.
Provides a comprehensive overview of forecasting principles and practice. It valuable resource for both students and practitioners who want to learn more about forecasting principles and practice.
Provides a comprehensive overview of forecasting methods, including both traditional and modern techniques. It valuable resource for both students and practitioners who want to learn more about forecasting.
Provides a comprehensive overview of time series analysis and forecasting. It valuable resource for both students and practitioners who want to learn more about time series analysis.

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