Data Analytics And Applications In The Fashion Industry

Learn Data Analytics and Business Analysis for the Fashion Industry. Build a Smart and Data-driven Fashion Company!

What you'll learn

How to apply data analytics in real-life

How data can help a fashion business

Industry-specific application of data analytics principles

Fashion analytics

Product recommendations

Consumer-driven marketing

Digital & web analytics

Integrated demand forecasting

Supply chain analytics for fashion companies

Store localization, clustering, and in-store optimization

Pricing optimization

AI for uncovering fashion trends

How to build a dashboard for a fashion company in Tableau

Requirements

No prior experience is required. We will start from the very basics

You'll need to install Tableau

Description

Business analytics and AI are two of the hottest topics in the fashion industry.Not only that: the global brands that rely on intelligent data collection and processing have a strong competitive advantage over the ones that are data blind.And this shouldn’t come as a surprise, right?We live in the 2020s.Today, in almost all industries, the most successful businesses leverage user data to extract meaningful insights and tailor their products to satisfy user wants and needs.Netflix recommends to us the movies and TV series we want to see next.Instagram knows which photos we want in our feed.So… naturally … fashion brands would want to know which clothes we want to wear, what impact the discounts have on us, and how likely it is that we’ll return after our first purchase.Top executives understand long-term gains in the fashion industry aren’t about one-off transactions. Instead, successful brands want to win us over for the long run. The best way to do that is by employing a strategy centered around hyper-personalization. This means leveraging analytics, data science, and AI to deliver a first-rate experience that will make us a repeated customer.Pretending that current fashion trends are the same as they were a decade ago is as detrimental as operating without leveraging insights from data. The best brands will surpass you because they will:Price items correctlyKnow when to discount an itemRecommend the right itemsExcel at engaging customers onlineStock the right stylesBe able to choose the right colors, fabrics, and sizesSupply stores on time and efficientlyThe goal of this course is to help you learn about analytics in the fashion industry. We want to help you understand the ways in which different types of analysis can be applied in the fashion world and why that would be helpful in practice.To provide invaluable insights that correspond to the best practices in the industry, we partnered with an experienced executive who’s worked with some of the biggest brands in the industry. His current work contract doesn’t allow us to share more info. However, his working title as Director of Data and Analytics for one of the biggest companies in the industry speaks volumes of his expertise of the topics we’ll cover together.This course is an invaluable opportunity for anyone who works in fashion or who wants to work in fashion and become a high-level executive. Moreover, the course can also be useful to data practitioners who would like to specialize/get hired in the fashion industry. Some of the interesting topics we will cover are:Product recommendationsConsumer-driven marketingDigital & web analyticsIntegrated demand forecastingSupply chain analytics for fashion companiesStore localization, clustering, and in-store optimizationPricing optimization, andAI for uncovering fashion trendsThis course offers tremendous upside for the time you will dedicate to it. Not only can it be career-changing if you work in fashion, but it can also inspire you to transform your business if you’re a fashion entrepreneur who wants to succeed in the years to come.

Overview

Section 1: Introduction  to The Course

Lecture 1 What Does the Course Cover?

Lecture 2 What Is Fashion Analytics?

Lecture 3 Realizing the Potential of Analytics in Fashion

Lecture 4 The Breadth of Analytical Options

Lecture 5 Requirements for Embedding Analytics in Fashion

Section 2: Consumer-Driven Marketing

Lecture 6 Marketing Fundamentals for Analytics

Lecture 7 Analytics Activation in Consumer-Driven Marketing

Lecture 8 An Overview of Cluster Analysis and Consumer Scoring

Section 3: Consumer Analytics - Product Recommendation

Lecture 9 What Is a Product Recommendation  Systems?

Lecture 10 Collaborative and Content-Based Filtering

Lecture 11 Similarity Measures for Product Recommendation  Engines

Section 4: Digital and Web Analytics

Lecture 12 Introduction to Digital and Web Analytics

Lecture 13 Experience Analytics and Attribution Models

Lecture 14 Clickstream Analytics and A/B Testing

Lecture 15 Challenges and Opportunities in Web Analytics

Section 5: Supply Chain Analytics

Lecture 16 Introduction to Supply Chain Analytics

Lecture 17 Advanced Analytics in the Supply Chain

Lecture 18 Applications of Analytics in the Supply Chain

Section 6: Integrated Demand Forecasting

Lecture 19 What Is Integrated Demand Forecasting?

Lecture 20 Integrated Demand Forecasting in the Fashion Industry

Lecture 21 Data Science in Demand Forecasting

Lecture 22 How Do Industry Leaders Use Using Integrated Demand Forecasting ?

Section 7: Pricing Optimization

Lecture 23 What Is Pricing Optimization?

Lecture 24 Advanced Analytics in Pricing Optimization

Lecture 25 How  Does the Fashion Industry Leverage Optimization in Pricing?

Section 8: Store Localization, Clustering, and In-store Optimization

Lecture 26 Introduction to Store Localization, Clustering, and In-store Optimization

Lecture 27 Advanced Analytics in Localization, Clustering, and In-store Optimization

Section 9: AI for Predicting Fashion Trends

Lecture 28 Introduction to Artificial Intelligence in Fashion

Lecture 29 Image Recognition and Market Intelligence in Fashion

Section 10: Case Study - Building a Fashion Analytics Story in Tableau

Lecture 30 Getting to Know the Dataset

Lecture 31 Creating a Company KPIs Table in Tableau - Net Sales

Lecture 32 Creating a Company KPIs Table in Tableau - Gross Profit Margins

Lecture 33 Creating a Map Chart of Consumer Countries in Tableau

Lecture 34 Creating a Customer KPIs Table in Tableau

Lecture 35 Creating a Bar Chart of Consumer Metrics in Tableau

Lecture 36 Building the Frequency Curve in Tableau

Lecture 37 Building the Repurchase Curve in Tableau

Lecture 38 Creating the Dashboards for the Fashion Analytics Story in Tableau

Lecture 39 Styling and Formatting the Fashion Analytics Report

Lecture 40 Interpretation of the Data Analytics Fashion Story

People who want to work in the fashion industry,Students of data analytics,People who want to work in the field of data analytics and want to learn how to apply their knowledge in practice,Aspiring data analysts,People who want to build a modern fashion brand,Fashion executives eager to incorporate data-driven decision making in their business