29.04.2021, 00:07
![[Bild: 5a3jofufbixb7ardlwibzrpjgn.jpg]](https://abload.de/img/5a3jofufbixb7ardlwibzrpjgn.jpg)
RA: Retail Customer Analytics and Trade Area Modeling.
MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 7.99 GB | Duration: 15h 42m
What you'll learn
Python
Customer analytics
Learn How to work daily with Python
Learn how to benefit from data to increase Customer Engagement.
Use K-means for Customer Segmentation.
Use Trade area modeling for Location and Competitive analysis.
Use Recommendation systems to Propose Products To customers.
Use Market Basket analysis to Make recommendations and Promotional Bundles to customers.
Predict Customer lifetime value of customers
Requirements
Basic Retail Knowledge
Python Crash courses are included.
Description
"Photo by Alexander Kovacs on Unsplash"
"This is one of the three courses in the Retail Series by RA, each course can be taken independently."
Master Retail management and analytics with Excel and Python
Retailers face fierce competition every day and keeping up with the new trends and customer preferences is a guarantee for excellence in the modern retail environment. one Keyway to excel in retail management is utilizing the data that is produced every day. It is estimated that We produce an overwhelming amount of data every day, roughly 2.5 quintillion bytes. According to an IBM study, 90% of the world's data has been created in the last two years.
Retail analytics is the field of studying the produced retail data and making insightful data-driven decisions from it. as this is a wide field, I have split the Program into three parts. in this course, we focus on the customer analytics part of retail. Understanding the customer is key for maintaining loyalty and developing products to boost retail business and profitability.
RA: Retail Customer Analytics and Trade Area Modeling.
1- Understanding the importance of customer analytics in retail.
2- Manipulation of Data with Pandas.
3-Working with Python for analytics.
5- Trade area modeling
6- Recommendation systems
7- Customer lifetime value prediction
8- Market Basket analytics
9- Churn prediction
Don't worry If you don't know how to code, we learn step by step by applying retail analysis!
*NOTE: Full Program includes downloadable resources and Python project files, homework and Program quizzes, lifetime access, and a 30-day money-back guarantee.
Who this Program is for:
· If you are an absolute beginner at coding, then take this Program.
· If you work in Retail and want to make data-driven decisions, this Program will equip you with what you need.
· If you are switching from Excel to a data science language. then this Program will fast-track your goal.
· If you are tired of doing the same analysis again and again on spreadsheets and want to find ways to automate it, this Program is for you.
Program Design
the Program is designed as experiential learning Modules, the first couple of modules are for retail fundamentals followed by Python programming fundamentals, this is to level all of the takers of this Program to the same pace. and the third part is retail applications using Data science which is using the knowledge of the first two modules to apply. while the Program delivery method will be a mix of me explaining the concepts on a whiteboard, Presentations, and Python-coding sessions where you do the coding with me step by step. there will be assessments in most of the sections to strengthen your newly acquired skills. all the practice and assessments are real retail use cases.
Who this course is for:
Retail Managers
Retail Analysts
Data Scientists
Data Analysts
Retail Strategist
Merchandizers
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/ra-retail-customer-analytics-and-trade-area-modeling/![[Bild: 16.summarysvoj7o.jpg]](https://abload.de/img/16.summarysvoj7o.jpg)
