Certified Retail Analytics Professional

How It Works

  1. 1. Select Certification & Register
  2. 2. Receive Online e-Learning Access (LMS)
  3. 3. Take exam online anywhere, anytime
  4. 4. Get certified & Increase Employability

Test Details

  • Duration: 60 minutes
  • No. of questions: 50
  • Maximum marks: 50, Passing marks: 25 (50%).
  • There is NO negative marking in this module.
  • Online exam.

Benefits of Certification

$49.00 /-
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Analytics involves data collection, processing, analysis and interpretation for better decision making and gain insights. Increased competition has put more focus on optimizing business processes and make informed business decisions. Analytics provide informed insights for effective decision making by data collation processing and analysis. Retail analytics is the upcoming technology which helps in increased retail sales and better inventory management.

The course covers

  • Basics of Analytics and statistics 
  • Using MS-Excel for analytics
  • Pricing Analytics
  • Retail Operations Analytics
  • Clustering Techniques
  • Customer Analytics

Why should I take Retail Analytics Certification?

This course is intended for retail professionals, managers, consultants and graduates wanting to excel in retail analytics. It is also well suited for those who are already working and would like to take certification for further career progression. Earning Vskills Certified Retail Analytics Professional Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.

How will benefit from taking this Certification?

Job seekers looking to find employment in retail, stores, inventory, retail management departments of various retail companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification.

Retail Analytics Table of Contents


Retail Analytics Practice Test


Retail Analytics Practice Test


Companies that hire Retail Analytics Professional

Retail Analytics Professionals are in great demand. Companies specializing in retail consultancy, analytics, and management, are constantly hiring skilled Vskills Certified Retail Analytics Professional. Various public and private companies also need Retail Analytics Professional for optimizing their retail operations.

Apply for Retail Analytics Certification

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Introduction to Retail Analytics

  • Overview of the Retail Industry
  • An Overview of Role of Analytics
  • Overview of Retail Data Sources
  • Data Collection and Preparation Techniques
  • Retail Analytics Applications
  • Retail Analytics Tools

Retail Data Collection and Preparation

  • Retail Data Sources
  • Data Collection Methods
  • Data Cleaning
  • Data Warehousing
  • Data Visualization
  • Data Security
  • Data Governance
  • Retail Data Preparation Case Studies

Using Spreadsheets for Analytics

  • Excel Formulas
  • Excel Functions
  • Spreadsheet Add-Ins
  • What is Spreadsheet Modeling

Visualizing Data in Spreadsheets

  • Excel Data Visualization Tools
  • Data Queries in Excel
  • Data Summarization in Excel
  • PivotTables and Pivot Charts

Descriptive Statistical Measures

  • Statistical Notation
  • Measures of Location
  • Measures of Dispersion
  • Measures of Shape
  • Measures of Association
  • Frequency Distributions
  • Excel Descriptive Statistics Tool

Probability Distributions

  • Probability Basics
  • Discrete Probability Distributions
  • Continuous Probability Distributions
  • Distribution Fitting

Sampling and Hypothesis

  • Statistics Basics
  • Data Basics
  • Measurement Systems
  • Some Basic Terms
  • Types of Sample Designs
  • Bases of stratification
  • Characteristics of a Good Sample Design
  • Determining the Sample Size

Data Processing and Analysis

  • Data Preparation
  • Data Validation
  • Data Editing
  • Coding
  • Tabulation
  • Data-Processing Methods

Introduction to Data Analytics

  • Origin of Data in Retail Analytics
  • Processes in Retail and Supply Chain Analytics
  • Analytical methods used in Retail Analytics
  • Use of Data Analytics and Decision-Making Models
  • Advanced Analytics in Retail
  • Overview of IoT (Internet of Things) and its application in Retail
  • Understanding Contemporary Analytics

Clustering Techniques in Retail Analytics

  • Introduction to Clustering
  • Types of Clustering Algorithms
  • K-means Clustering
  • Hierarchical Clustering
  • Density-based Clustering
  • Model-Based Clustering
  • Clustering Evaluation Metrics
  • Applications of Clustering in Retail Analytics
  • Limitations and Challenges of Clustering Techniques

Customer Analytics

  • Introduction to Customer Analytics
  • Customer Data Collection and Management
  • Customer Segmentation
  • Customer Profiling
  • Customer Lifetime Value
  • Customer Churn Analysis
  • Customer Behavior Analysis
  • Customer Feedback Analysis
  • Customer Journey Mapping
  • Applications of Customer Analytics

Introduction to Pricing Analytics

  • Price Elasticity of Demand
  • Competitor Pricing Analysis
  • Customer Segmentation
  • Price Optimization
  • Price Perception
  • Price Psychology
  • Price Discrimination
  • Price Bundling
  • Promotional Pricing
  • Value-Based Pricing

Introduction to Marketing Analytics

  • Marketing Mix Modeling (MMM)
  • Customer Acquisition Cost (CAC)
  • Customer Retention and Churn
  • Marketing Attribution
  • A/B Testing
  • Predictive Analytics
  • Web Analytics
  • Social Media Analytics

Introduction to Retail Operations Analytics

  • Process of Inventory Management
  • Supply Chain Analytics
  • Store Operations
  • Price Optimization
  • Customer Demand Forecasting
  • Sales and Promotion Analysis
  • Labor Optimization
  • Loss Prevention
  • Customer Analytics
  • Retail Performance Metrics

Understanding Retail Technology

  • Point of Sale (POS) Systems
  • E-commerce Platforms
  • Customer Relationship Management (CRM) Systems
  • Inventory Management Systems
  • Supply Chain Management Systems
  • Mobile Technology
  • Data Analytics
  • Artificial Intelligence (AI) and Machine Learning (ML)
  • Explain Process of Automation
  • Augmented Reality (AR) and Virtual Reality (VR)

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