Revenue and Pricing Analytics with Excel & Python.
Revenue and Pricing Analytics with Excel & Python., available at $59.99, has an average rating of 4.58, with 158 lectures, 3 quizzes, based on 213 reviews, and has 17418 subscribers.
You will learn about What are the discount rates you should set to maximize revenue of your products? Optimizing prices with excel and python Customized pricing with python Customer analytics The different pricing strategies that you should implement for different products. The willingness to pay of customers how to fit the demand with the right response function How to differentiate products and pricing to different segments The concept of nesting in revenue management and how to apply it Retail Profit Data Science Python This course is ideal for individuals who are Marketing professionals or Sales professionals or Revenue managers or Brand Managers or Entrepreneurs or Supply chain professionals It is particularly useful for Marketing professionals or Sales professionals or Revenue managers or Brand Managers or Entrepreneurs or Supply chain professionals.
Enroll now: Revenue and Pricing Analytics with Excel & Python.
Summary
Title: Revenue and Pricing Analytics with Excel & Python.
Price: $59.99
Average Rating: 4.58
Number of Lectures: 158
Number of Quizzes: 3
Number of Published Lectures: 158
Number of Published Quizzes: 3
Number of Curriculum Items: 161
Number of Published Curriculum Objects: 161
Original Price: $84.99
Quality Status: approved
Status: Live
What You Will Learn
- What are the discount rates you should set to maximize revenue of your products?
- Optimizing prices with excel and python
- Customized pricing with python
- Customer analytics
- The different pricing strategies that you should implement for different products.
- The willingness to pay of customers
- how to fit the demand with the right response function
- How to differentiate products and pricing to different segments
- The concept of nesting in revenue management and how to apply it
- Retail
- Profit
- Data Science
- Python
Who Should Attend
- Marketing professionals
- Sales professionals
- Revenue managers
- Brand Managers
- Entrepreneurs
- Supply chain professionals
Target Audiences
- Marketing professionals
- Sales professionals
- Revenue managers
- Brand Managers
- Entrepreneurs
- Supply chain professionals
Course Image by @agent_illustrateur-Christine Roy from unsplash.
Python Crash section included!
in the late seventies, airline ticket prices in the united states were regulated and almost fixed, we as customers did not have the luxury to opt for economy class or business class, only one class!! Back thenAmerican airlines were the leaders in the industry. But with deregulation new disruptors asPeople Express entered the scene with tickets so much cheaper thanAmerican Airlines. Customers migrated from American airlinesto the economicPeople Express.
what happened next changed the way we think about prices from merely making a profit to a strategic weapon that boosts business profitability and enhances product availability.
American Airlines introduced segmentation and revenue management techniques on its ticket prices “yield management” to attract People Express Customers back and People Expresseventually went out of business. oh, I forgot to mention that American airlines’ profit increased by 47% that year. And the rest was history.
This practice was then adopted by Ford for car rentals, Mariott hotels for room booking, NBC, and ABC for Ads placement to pretty much every business there is nowadays.
this course will take you on this exciting journey of understanding consumer behavior. how to set prices for your products to maximize revenue and enhance product availability. if you are running your own business, managing a product line, or even launching a new product or service, this course will come in handy to set you on the right path for success.
Not only this, Businesses now have hundreds of products and services if not thousands and we simply cannot optimize pricing for all of them with excel for example, that’s why the course introduces you also pricing and revenue management with Python. not to worry if it’s the first time for you with python, I show you how to do it step by step.
the course is full of lectures, concepts, codes, exercises, and spreadsheets. and we don’t present the code, we do the code with you, step by step, by the end of this course, you will be able to :
With excel :
-
The perishability of inventory
-
The different pricing strategies
-
The willingness to pay of customers
-
how to fit the demand with the right response function
-
Elasticity of products and how can we use them to set prices
-
How to differentiate products and pricing to different segments
-
The concept of nesting in revenue management and how to apply it
-
Applying little wood’s rule and EMSR to set booking limits for different service offering
-
Optimizing the prices for different product simultaneously
-
Markdowns
With python :
Þ The basics of python, functions, and for loops
Þ Fitting demand with linear and logit functions
Þ Multi-product optimization
Þ Customized pricing.
Course Design
the course is designed as experiential learning Modules, the first couple of modules are for understanding pricing followed by applications using optimization.Don’t worry if you don’t know python, there are is a python fundamental section in the course to get you up and running with python.
Looking forward to seeing you inside and hope you enjoy the class.
Happy Mining!
Haytham
Rescale Analytics
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: What is pricing?
Lecture 3: History of Pricing.
Lecture 4: Internal dimensions of price.
Lecture 5: A perfectly Competitive market
Lecture 6: The price market Dynamics
Lecture 7: The early adaptors
Lecture 8: Products Vs Services Vs Resources.
Lecture 9: Characteristics of the service industry
Lecture 10: Game changer
Lecture 11: ERP systems
Lecture 12: The evolution of E-commerce
Lecture 13: Different pricing strategies
Lecture 14: Price Dimension
Lecture 15: Some Examples
Chapter 2: Price Response function, Willingness to pay and Elasticity.
Lecture 1: Intro
Lecture 2: Linear Regression
Lecture 3: Price Response function
Lecture 4: Logistic Regression
Lecture 5: Logistic Price Response function
Lecture 6: Linear Price function estimation
Lecture 7: Correction
Lecture 8: Logit Price function
Lecture 9: Simulating the price
Lecture 10: Elasticity intro
Lecture 11: Elasticity
Lecture 12: Elasticity for logit and linear
Lecture 13: Assignment
Lecture 14: Answer
Lecture 15: Some examples of elasticity
Lecture 16: Response function variants- Polynomial
Lecture 17: Willingness to pay
Lecture 18: Point of maximum profit
Lecture 19: Summary Quick Functions
Lecture 20: Logit and linear solver optimization
Lecture 21: Summary
Chapter 3: Price Differentiation
Lecture 1: Segmentation Intro
Lecture 2: Grouping Customers
Lecture 3: A practical example
Lecture 4: Realized Profit
Lecture 5: Profit with segmentation and without segmentation
Lecture 6: Segmentation simulation 1
Lecture 7: Segmentation simulation 2
Lecture 8: assignment
Lecture 9: Answer 1
Lecture 10: Answer 2
Lecture 11: Group pricing
Lecture 12: Channel segmentations and Cupons
Lecture 13: Volume Discounts
Lecture 14: Volume discount Example
Lecture 15: Optimizing profit with supply constraints
Lecture 16: Variable Pricing
Lecture 17: Non Variable pricing optimization
Lecture 18: Variable pricing optimization
Lecture 19: Assignment
Lecture 20: Variable pricing answer
Chapter 4: Revenue management
Lecture 1: Revenue Management Intro
Lecture 2: Revenue management
Lecture 3: The rest is History.
Lecture 4: Allotment
Lecture 5: Nesting
Lecture 6: Revenue management Components and techniques
Lecture 7: Capacity allocation
Lecture 8: Littlewood example
Lecture 9: Assignment
Lecture 10: Answer
Lecture 11: Multiple-class Fare EMSR-a
Lecture 12: EMSR-a example
Lecture 13: Assignment
Lecture 14: Answer
Lecture 15: Network management
Lecture 16: airplane example
Lecture 17: Linear programming 1
Lecture 18: Linear programming 2
Lecture 19: Overbooking
Lecture 20: Network management assignment
Lecture 21: Network management answer
Lecture 22: Python intro
Chapter 5: Installing Anaconda
Lecture 1: Python History
Lecture 2: Downloading Anaconda
Lecture 3: Installing Anaconda
Lecture 4: Spyder Overview
Lecture 5: Jupiter overview
Lecture 6: Packages
Lecture 7: Inventorize Package
Chapter 6: Python Crash section
Lecture 1: Intro
Lecture 2: Dataframes
Lecture 3: Arithmetic Calculations with Python
Lecture 4: Lists
Lecture 5: Dictionaries
Lecture 6: Arrays
Instructors
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Haytham Omar-Ph.D
Consultant-Supply chain
Rating Distribution
- 1 stars: 5 votes
- 2 stars: 10 votes
- 3 stars: 23 votes
- 4 stars: 39 votes
- 5 stars: 136 votes
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