RA: Retail Planning,Assortment Analytics with Excel & Python from Udemy

New update : Forecast for OTB calculation with AutoML is added (Aug 2023)

"This is one of the three courses in the Retail Series by RA, each course can be taken independently."

Master Retail planning 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.

Retail Planning and assortment analytics with Excel & Python.

1- Retail Metrics

2- Metrics in Python.

3- Budgeting.

4- Retail Planning in Python.

5- Retail Buying.

6- Assortment Optimization.

7- Managing Retail Inventory with Python.

8- Managing stocks based on Types.

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 metrics 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.

What's inside

Learning objectives

Make a retail budget from a-z
Otb
Learn python and analytics
Merchandising
Assortment planning
Optimization
Python
Excel
Metrics
Operations

Conversion rate
Merchandise
Retail
Inventory
Consignment
Budget
Budgeting
Assortment
Show more
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Make a retail budget from a-z
Otb
Learn python and analytics
Merchandising
Assortment planning
Optimization
Python
Excel
Metrics
Operations
Conversion rate
Merchandise
Retail
Inventory
Consignment
Budget
Budgeting
Assortment
Show more
Show less

Syllabus

Installing Anaconda

Retail Metrics

Introduction

Curriculum

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers retail metrics, budgeting, and assortment optimization, which are essential for professionals aiming to improve retail performance through data-driven strategies

Explores retail planning and assortment analytics using both Excel and Python, catering to users of both tools and facilitating a transition from Excel to Python

Includes hands-on Python coding sessions and downloadable project files, providing practical experience in applying data science techniques to real-world retail scenarios

Teaches the use of Python libraries and packages relevant to retail analysis, such as those for inventory management, which can automate repetitive tasks

Requires learners to install Anaconda, which may require some learners to upgrade their systems or learn to use a new platform

Features an update that includes forecasting for OTB (Open to Buy) calculation with AutoML, which is a growing trend in retail analytics and planning

Reviews summary

Practical retail analytics with excel & python

According to students, this course offers a practical introduction to retail analytics, especially for those new to using Python for data analysis in a retail context. Learners appreciate the focus on real-world retail problems and how the course integrates Excel and Python applications. While many find it a good starting point, some suggest that certain topics could benefit from more in-depth coverage, and a few encountered minor issues or outdated elements. Overall, it's seen as a valuable resource for bridging the gap from spreadsheets to data-driven retail decision-making and is largely positively received.

Clear explanations of retail metrics.

"The explanations of retail metrics like OTB, inventory turnover, and margin were very clear."

"I finally understood the logic behind these retail calculations thanks to the course."

"It provides a solid foundation in key retail concepts before diving into the tools."

Accessible introduction for non-coders.

"As someone completely new to coding, the step-by-step Python lessons were surprisingly easy to follow."

"The course successfully teaches you enough Python to get started with retail analytics tasks quickly."

"It was a great way to learn Python specifically for data tasks relevant to my retail career."

"I appreciated how they started with basic Python and built up the retail examples."

Focuses on real-world retail use cases.

"I could immediately apply the concepts and Python scripts to my work in retail planning."

"Using real retail data for the assignments made the learning very relevant and practical."

"The focus on real-world retail scenarios and data analysis was incredibly helpful for my job."

"Seeing how to apply Excel concepts and transition them to Python was highly valuable."

Some errors or outdated parts noted.

"Ran into a few errors following the Python code in the lectures; some packages or syntax might be slightly outdated."

"A couple of the lectures felt slightly outdated compared to current retail software or practices."

"Had to troubleshoot some code snippets myself, which was frustrating at times."

"Found a few inconsistencies between lecture explanations and the provided resources."

Some topics feel covered superficially.

"The Python crash course is quite basic; you'll likely need more resources for deeper understanding of the language."

"I wish there was more advanced content on optimization techniques or forecasting models in Python."

"Covers a wide range of topics but doesn't go very deep into any single advanced area."

"Good for a broad overview, but don't expect mastery from this alone."

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 RA: Retail Planning,Assortment Analytics with Excel & Python with these activities:

Review Excel Fundamentals

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Refresh your knowledge of Excel fundamentals to better understand the retail planning and analytics concepts covered in the course.

Browse courses on Excel

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Review basic Excel functions like SUM, AVERAGE, and COUNT.
Practice creating charts and graphs to visualize data.
Familiarize yourself with pivot tables for data summarization.

Brush Up on Python Basics

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Review Python basics to prepare for the Python-based retail analytics exercises in the course.

Browse courses on Python

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Review data structures like lists, dictionaries, and dataframes.
Practice writing basic Python functions and loops.
Familiarize yourself with Pandas for data manipulation.

Read 'Retail Analytics: The Big Picture'

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Gain a broader understanding of retail analytics concepts and applications.

View Alter Ego: A Novel on Amazon

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Read the book and take notes on key concepts and examples.
Reflect on how the concepts relate to your own retail experience.

Four other activities

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Practice Python Data Manipulation

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Reinforce your Python skills by working through data manipulation exercises relevant to retail data.

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Find retail datasets online (e.g., Kaggle) or create your own synthetic data.
Practice cleaning, transforming, and analyzing the data using Pandas.
Experiment with different data manipulation techniques covered in the course.

Create a Retail Dashboard in Excel

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Apply your Excel skills to create a dashboard that visualizes key retail metrics.

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Gather relevant retail data (e.g., sales, inventory, customer data).
Design a dashboard layout that effectively communicates key insights.
Use Excel charts, graphs, and pivot tables to visualize the data.
Add interactive elements like slicers and filters.

Build a Retail Sales Forecasting Model

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Develop a sales forecasting model using Python to predict future sales based on historical data.

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Gather historical sales data and relevant external factors (e.g., promotions, seasonality).
Explore different forecasting techniques (e.g., time series analysis, regression).
Implement the chosen technique in Python using libraries like scikit-learn.
Evaluate the model's performance and refine it as needed.

Read 'Data Science for Retail: Modern Data Mining and Machine Learning Techniques'

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Explore advanced data science techniques for retail applications.

View Alter Ego: A Novel on Amazon

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Read the book and take notes on key concepts and algorithms.
Identify potential applications of these techniques in your own retail context.

Career center

Learners who complete RA: Retail Planning,Assortment Analytics with Excel & Python will develop knowledge and skills that may be useful to these careers:

Retail Analyst

A retail analyst examines sales data, consumer behavior, and market trends to provide insights that drive business decisions. Their work helps optimize pricing, promotions, and inventory management. This course provides retail analysts with the skills to extract actionable insights from complex datasets. The comprehensive curriculum covers essential retail metrics and Python programming. Learning to use Python is crucial for automating data analysis, building predictive models, and creating insightful visualizations. The course's focus on retail-specific applications, such as assortment optimization and inventory management, makes it uniquely valuable for aspiring retail analysts looking to harness the power of data to drive success in the retail industry.

See salaries and explore the career path for Retail Analyst

Assortment Planner

An assortment planner is responsible for curating the right mix of products to meet customer demand and maximize sales. The role requires analyzing sales data, identifying trends, and understanding customer preferences to create a cohesive and profitable product selection. For those aspiring to become an assortment planner, this course provides a solid foundation in retail analytics. The course covers assortment optimization and teaches how to utilize retail metrics and Python to analyze sales data, forecast demand, and identify the most profitable product combinations. By mastering these analytical skills, a prospective assortment planner can make data-driven decisions that drive sales and improve profitability. The course's emphasis on practical applications and real-world case studies is especially valuable for developing the skills needed to succeed in this role.

See salaries and explore the career path for Assortment Planner

Retail Planner

A retail planner develops strategies to maximize sales and profitability. The role involves analyzing market trends, consumer behavior, and sales data to create effective plans for purchasing, pricing, and promoting merchandise. This course equips aspiring retail planners with the tools to excel in this data-driven environment. With modules covering retail metrics, budgeting, and planning in Python, the course helps build skills in analyzing key performance indicators, developing financial forecasts, and optimizing inventory levels. The focus on assortment optimization is directly relevant to creating product mixes that meet customer demand and maximize revenue. Furthermore, learning Python helps automate repetitive tasks and perform more sophisticated analyses, such as forecasting demand and identifying optimal pricing strategies, making this course a strategic asset for any prospective retail planner.

See salaries and explore the career path for Retail Planner

Category Manager

A category manager oversees a specific product category within a retail organization. Responsibilities include selecting products, negotiating with suppliers, developing marketing plans, and managing inventory levels. This course helps individuals in the role of category manager. The course covers retail planning, assortment analytics, and inventory management. The knowledge of excel and Python gives category managers the skills to analyze data, optimize product selections, and improve profitability within their respective categories.

See salaries and explore the career path for Category Manager

Inventory Analyst

An inventory analyst is responsible for managing and optimizing inventory levels to meet customer demand while minimizing costs. This role requires analyzing sales data, forecasting demand, and developing strategies to ensure the right products are available at the right time. If you are considering a role as an inventory analyst, this course may provide valuable skills and knowledge. The course covers inventory management with Python and teaches how to use retail metrics to track inventory performance. The inclusion of Python programming helps in automating inventory tracking, forecasting demand, and identifying optimal order quantities. The course’s emphasis on retail-specific applications makes it particularly helpful for developing the skills needed to excel as an inventory analyst.

See salaries and explore the career path for Inventory Analyst

Pricing Analyst

A pricing analyst determines optimal pricing strategies to maximize revenue and profitability. This involves analyzing market trends, competitor pricing, and customer demand to set prices that are competitive and attractive to customers. For those interested in a pricing analyst role, this course helps develop skills in data analysis and Python programming. The course covers essential retail metrics and teaches how to use Python to build pricing models, analyze sales data, and forecast demand. The course's focus on practical applications and real-world case studies is especially valuable for developing the skills needed to succeed in this role.

See salaries and explore the career path for Pricing Analyst

Demand Planner

A demand planner forecasts future demand for products to ensure that the organization can meet customer needs without overstocking or running out of inventory. The role involves analyzing sales data, market trends, and promotional activities to develop accurate demand forecasts. This course provides the foundation for aspiring demand planners. The course covers retail metrics and inventory management, giving the learner the ability to use Excel and Python. The learner will be able to optimize inventory levels by producing data-driven forecasts.

See salaries and explore the career path for Demand Planner

Merchandise Planner

A merchandise planner develops and executes strategies to maximize sales and profitability through effective product selection, pricing, and promotion. This role requires a strong understanding of market trends, customer behavior, and financial planning. For those aspiring to a career as a merchandise planner, this course may be a valuable resource. The course covers retail planning, assortment analytics, and the use of Python for data analysis, which are all essential skills for merchandise planning. Learning budgeting techniques helps in developing financial plans, while assortment planning and optimization skills are crucial for selecting the right products. The course's emphasis on real-world retail applications makes it particularly relevant for developing the practical skills needed to succeed as a merchandise planner.

See salaries and explore the career path for Merchandise Planner

Business Intelligence Analyst

A business intelligence analyst analyzes data to identify trends, patterns, and insights that can improve business performance. The analysis often involves gathering data from various sources, cleaning and transforming it, and creating reports and dashboards to communicate findings to stakeholders. Aspiring business intelligence analysts will find this course relevant to their career goals. The course covers retail metrics, data analysis, and the use of Python for data visualization which are all essential skills for business intelligence. The course's focus on real-world retail applications makes it particularly valuable for developing the skills needed to succeed as a business intelligence analyst in the retail industry.

See salaries and explore the career path for Business Intelligence Analyst

E-commerce Analyst

An ecommerce analyst analyzes website traffic, sales data, and customer behavior to identify opportunities to improve the online shopping experience and increase sales. The role requires strong analytical skills, as well as a solid understanding of ecommerce principles. The insights gained in this course may be useful if you are considering a career as an ecommerce analyst. The course covers retail metrics, data analysis, and the use of Python for data analysis which will help analysts with data-driven decisions. The course's emphasis on real-world retail applications makes it particularly valuable for developing the skills needed to succeed as an ecommerce analyst in an online setting.

See salaries and explore the career path for E-commerce Analyst

Supply Chain Analyst

A supply chain analyst optimizes the flow of goods from suppliers to customers. The optimization involves analyzing data, identifying inefficiencies, and developing solutions to improve the speed, cost-effectiveness, and reliability of the supply chain. If you are considering a career as a supply chain analyst, this course may be helpful. The course covers retail metrics, inventory management, and the use of Python for data analysis. The inclusion of Python helps in automating data analysis, forecasting demand, and optimizing inventory levels. This course's focus on real-world retail applications makes it particularly relevant for developing the skills needed to excel as a supply chain analyst in the retail sector.

See salaries and explore the career path for Supply Chain Analyst

Data Scientist

A data scientist uses advanced analytical techniques to extract insights and solve complex problems. This role requires a strong background in statistics, mathematics, and computer science, as well as experience with data analysis tools and techniques. Data scientists may find this course to be a useful introduction to retail analytics. While a data scientist role typically requires an advanced degree, this course covers retail metrics, data analysis, and the use of Python for data science. The inclusion of Python helps in automating data analysis, building predictive models, and creating insightful visualizations. The course's focus on real-world retail applications makes it particularly relevant for data scientists working in the retail sector.

See salaries and explore the career path for Data Scientist

Market Research Analyst

A market research analyst studies consumer behavior, market trends, and competitor activities to provide insights that inform marketing and product development decisions. This role requires strong analytical skills, as well as the ability to communicate findings effectively to stakeholders. Aspiring market research analysts might find this course helpful in honing their analytical skills. The course covers retail metrics, data analysis, and the use of Python for data visualization. The inclusion of Python helps in automating data analysis, building predictive models, and creating insightful visualizations. The course's focus on real-world retail applications makes it particularly relevant for market research analysts working in the retail sector.

See salaries and explore the career path for Market Research Analyst

Financial Analyst

A financial analyst evaluates financial data, prepares reports, and provides recommendations to guide investment decisions. The role requires strong analytical and problem-solving skills, as well as a solid understanding of financial principles. This course may be useful if you are considering a career as a financial analyst. The course covers retail metrics, budgeting, and the use of Python for data analysis. Learning budgeting techniques is directly relevant to financial planning. The course's emphasis on real-world applications makes it particularly relevant for developing the practical skills needed to succeed as a financial analyst in the retail industry.

See salaries and explore the career path for Financial Analyst

Operations Analyst

An operations analyst improves efficiency and effectiveness of an organization's processes. The role requires a focus on data analysis, process improvement, and problem-solving. The use of retail metrics and Python is important, and this course may be helpful if you are considering this role. The course covers retail metrics, data analysis, and the use of Python for data analysis. Also, developing data-driven decisions improves operational processes. The course's emphasis on real-world retail applications makes it particularly relevant for developing the practical skills needed to succeed as an operations analyst.

See salaries and explore the career path for Operations Analyst

Reading list

We've selected one 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 RA: Retail Planning,Assortment Analytics with Excel & Python.

Alter Ego

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Provides a broad overview of retail analytics, covering various applications and techniques. It helps to understand the strategic importance of data-driven decision-making in retail. While not a coding book, it provides valuable context for the analytical methods used in the course. It is useful as additional reading to provide a broader understanding of the field.

Alter Ego: A Novel

Paperback

RA

Retail Planning,Assortment Analytics with Excel & Python

What's inside

Learning objectives

Syllabus

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Reviews summary

Practical retail analytics with excel & python

Activities

Career center

Reading list

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