Course Description-

This course on Retail Analytics will teach you some of the important concepts as given below:

• Understanding of what retail analytics is?
• Understanding the Product terminology
• Retail definitions and type of Retailers
• Retail Channel and Formats
• Merchandise Category its uses and Functionality in Retail Environment.
• Retail Articles its uses and different types of Articles like Single , Generic and Sales Set.
• How Retail Supply chain works and Key Stake holders associated with Retail Supply chain
• Entire Supply Chain Process and different document types in supply chain
• Retail Assortment basic and its uses
• Different type of retail channels in depth along with pros and cons of each
• How multi-channel help retailer and how a brick and mortar retailer can develop multi-channel strategy
• Retail Dashboard understanding , working on Score card and dashboard along with data, dimensions , KPI etc.
• Using utilities to build dashboard covered utility like graphs, grids, maps, heat maps and networks
• Recency Frequency and Monetary value segmentation Introduction and methods to build .
• Building Model , Examples and application of RFM
• Market Basket Analysis Introduction and Key Metrics Support , Confidence , Lift and Affinity
• Building Model , Examples and application of MBA
•  Key Retail issues across the board and how each stake holders like CEO , Operation Head , Category and Buying Team look  at information
• Business Challenge associated with retail process are covered . Complete retail cycle and key process required for building scorecard.
• How to build dashboard for Store , Merchandise, Promotion and inventory. Key process like Ageing analysis , Open to buy , store comparison being covered.
• How to build dashboard for Loss Prevention , Assortment , Pricing and Placement process. Also to build different scenarios for retail environment
• Retail scenario and its usage along with data visualization techniques like Heat map , leader board and live dashboard to build successful story out of data.
• Store Clustering Techniques based on scientific method like customer price senstivity, geography and demographics. Learn about advantages and service deliverables for store clustering
• Uses of geography data for store clustering. Example of retail company, concept , zones , city and stores. How Org structure are build for retail organisation
• Understanding the business problem and how to decompose into analytics problem. How to identify stack holders and work upon real life retail case study.
• How to use case study learning in identifying other retail problems .
• Working on real data and how to interpret meaningful information. Specific column like billno, customer data have been taught
• Working on real data and how to interpret meaningful information. Specific column like Product category and how to find duplicates. Summary build with help of pivot to work upon data.
• How to use customer data and build recency score from the given data set. Classified customers in High , medium and low buckets to build Final RFM model
• How to use customer data and build Frequency and monetary score from the given data set. Classified customers in High , medium and low buckets to build Final RFM model
• How to build category dashboard and data visualization techniques
• Customer recommendation and segmentation along with personalization to increase sales and retain loyal customers
• Category Specific recommendation in terms of merchandise , customer and pricing strategy

What are the requirements?

• Basic knowledge of the analytics methodology
• Knowledge of popular analytic techniques such as regression and clustering will be helpful

What am I going to get from this course?

• Get an intuitive understanding of retail as a business.
• Get knowledge of how analytics and its applications help the retail industry

What is the target audience?

• Professionals who are looking to pick up retail analytics skills
• MBA Students/Recent engineering or other graduates who want to make a career in retail analytics.
• Retail Professional who wants to sharpen their Analytics skills.
• E -commerce Professionals

Curriculum

Section 1: Introduction

1                  Introduction to Retail Analytics

2                  Introduction to Retail Analytics continued

3                  Retail Overviews Part 1

4                  Retail Overviews Part 2

5                  Retail Overviews Part 3

6                  Retail Overviews Part 4

7                  Product Terminology Part 1

8                  Product Terminology continued

9                  Supply Chain Terminology

10               Supply Chain Terminology continued

11               Assortmet Terminology

Section 2: Multi Channel Retail

12               Different type of retail channels

13               How multi channel help retailer

14               How a brick and mortar retailer can developed multi channel strategy

15               Retail Dashboard

16               Retail Dashboard continued

17               Recency Frequency and Monetary value segmentation

18               Recency Frequency and Monetary value segmentation continued

19               Building Model , Examples and application of RFM

20               Building Model , Examples and application of RFM continued

21               Retail analytics MBA Methodology Part 01

22               Retail analytics MBA Methodology Part 02

23               Retail analytics MBA Methodology 2

24               Category Score Card Part 1

25               Category Score Card Part 2

26               Category Score Card Part 3

27               Category Score Card Part 4 part-1

28               Category Score Card Part 4 part-2

29               Category Score Card Part 4

30               Category Score Card Part 5

31               Category Score Card Part 6

32               Store Clustering Part 1_Part 01

33               Store Clustering Part 1_Part 02

34               Store Clustering Part 2

Section 3: Retail Case Study

35               Case Study Part 1

36               Case Study Part 2

37               Data Understanding Part 1- Part-1

38               Data Understanding Part 1- Part-2

39               Data Understanding Part 2

40               Data modelling part 1

41               Data modelling part 2 Part-1

42               Data modelling part 2 Part-2

43               Data modelling part 3

44               Recommendation Part 1- Part-1

45               Recommendation Part 1- Part-2

46               Recommendation Part 2- Part-1

47               Recommendation Part 2- Part-2

Benefits of online course:

1. High Quality Content

2. Learn Anywhere Anytime & at Your Pace

3. 24X7 Customer Support

4. Complete Student Support throughout the Program

5. Online Video Training Material

6. Lifetime course access

For any Query call -

Mob - +918587999769