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Revenue and Pricing Analytics with Excel & Python

Revenue and Pricing Analytics with Excel & Python

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz
Language: English | SRT | Size: 6.77 GB | Duration: 12h 37m

What you'll 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
Basic Knowledge of excel
Motivation to increase revenue and profits.
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 then American airlines were the leaders in the industry. But with deregulation new disruptors as People Express entered the scene with tickets so much cheaper than American Airlines. Customers migrated from American airlines to the economic People 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 Express eventually 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 :

Þ The perishability of inventory

Þ The different pricing strategies

Þ The willingness to pay of customers

Þ how to fit the demand with the right response function

Þ Elasticity of products and how can we use them to set prices

Þ How to differentiate products and pricing to different segments

Þ The concept of nesting in revenue management and how to apply it

Þ Applying little wood’s rule and EMSR to set booking limits for different service offering

Þ Optimizing the prices for different product simultaneously

Þ 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!


Rescale Analytics

Who this course is for:
Marketing professionals
Sales professionals
Revenue managers
Brand Managers
Supply chain professionals


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