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February 13, 2024
Here are the top 3 Retail Analytics Data Story use cases every beginner should know.
But before we begin, if you're someone who wants to build projects for Data Science Portfolio then keep your tabs on what's happening in the world of Data Science & Businesses, and Hit EARLY ACCESS if you haven't already.
If you already have Early Access, you can just go ahead and read our Data Story! 😀
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Are you someone who want to boost your resume and stand out in the job market? One of the coolest ways is by diving into some cool Domain related Data Analytics projects.
And guess what?
We've got just the thing for you – Super AI!
Super AI is Your Co-Pilot here to help you come up with great ideas, tell captivating stories with your data, create awesome data stories and AI generated insights that'll wow everyone.
So, what kind of projects are we talking about?
Well, In this post we’ll be talking about 3 Retail Data Analytics Project Ideas for Beginners which are :
Exciting, right?
Oh, and here's the best part – all these projects were done using a popular Superstore Dataset available on Kaggle.
Getting started with Super AI is like taking the coolest ride in town. We're talking about making Exploratory Data Analysis (EDA) a breeze – and get this, no need to write a single fancy query. It's like magic, but with data!
Here is what you should look forward to
Let’s Inspect our dataset. This dataset got all the deeds on sales – order IDs, order and shipping dates, shipping mode, customer names and where they're at, plus product info like category and name. And of course, we've got the numbers – sales amount, quantity, discounts, and profit.
This data enables analysis of sales performance, profitability, and customer behavior to improve supply chain management decisions. Here are some sample Rows & Columns of the Superstore Dataset.
As an aspiring data analyst, if you want to do Hands-on projects related to Retail Domain, you’ll need to demonstrate a few key skills in your portfolio. These data analytics project ideas reflect the tasks often fundamental to many data analysis roles.
In this retail sales analysis project, we're basically exploring sales data, checking out what customers are up to, and seeing how fast stuff flies off the shelves. With Super AI's cool data visuals, we're hoping to figure out things like when sales peak, which products rock and how our marketing tricks pay off. Here are 4 steps to create the following Use Case
Let's say, for this use case our Business User will be - Superstore Sales Manager. We will look into the data with a sales manager perspective so that we have a starting point on how we perceive the data.
Once, let's get into the mind of our Superstore Sales Manager with an Empathy Map:
And now, let’s define the objective based on the Sales Manager Empathy Map
Objective : The objective of the Superstore Sales & Profit project is to provide a comprehensive and visually intuitive analysis of the sales and profitability metrics within the superstore.
On the basis of User's Pain & Gain and Objective, we'll target the KPI's. They are as follows:
Finally, let's ask some burning questions during our Exploratory Data Analysis (EDA):
1. What is the overall performance in terms of sales, profits, and discounts?
2. How do these metrics change over the years?
3. Are there any specific categories that we can focus on to improve our performance?
4. How were discounts offered by regions in 2022?
This project focuses on optimizing logistics and customer satisfaction. Through advanced data visualization, it examines shipping times, costs, and order fulfillment efficiency to streamline operations, reduce costs, and enhance overall shipping performance in the retail superstore.
Let's say, for this use case our Business User will be - Logistics Optimization Manager
Once, let's get into the mind of our Logistics Optimization Manager with an Empathy Map:
And now, let’s define the objective based on the Logistics Optimization Manager Empathy Map
Objective : The objective is aimed at delving into shipping data to enhance cost-effectiveness and operational efficiency. Shipping costs are a substantial expenditure for businesses, and optimizing these costs is crucial for overall financial performance.
Next, let's measure success with some KPIs:
Finally, let's ask some burning questions during our Exploratory Data Analysis (EDA):
1. What Are My Sales And Profit By Ship Mode?
2. How Are My Sales And Profit Performing Yearly On Same-Day Ship Mode?
3. Which Region Is Not Performing On Same-Day Mode In 2023?
4. What Is Category Wise Impact In South Region In Year 2023?
5. Technology Subcategory Profit And Sales In South Region Same Day 2023?
This project aims to provide comprehensive insights into customer behavior, preferences, and buying patterns. Utilizing advanced data visualization, this project will analyze customer demographics, purchase history, and engagement metrics to enhance marketing strategies, personalize customer experiences, and improve overall retail performance.
Let's say, for this use case our Business User will be - Customer Insight Manager
Once, let's get into the mind of our Customer Insight Manager with an Empathy Map:
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And now, let’s define the objective based on the Customer Insight Manager Empathy Map
Objective : The objectives include identifying opportunities for upselling, collaborating with cross-functional teams, and aligning marketing strategies with evolving customer expectations.
On the basis of User's Pain & Gain and Objective, we'll target the KPI's. They are as follows:
Finally, let's ask some burning questions during our Exploratory Data Analysis (EDA):
1. What are the key characteristics and behaviors of the top 10 customers contributing to the highest sales in 2023?
2. Are there specific regions where the concentration of high-sales customers is more pronounced?
3. Are there states where the top customers contribute significantly to overall sales?
4. What insights can be gained by examining the top 5 customers based on different shipping modes?
We at Super AI are on a mission to tell #1billion #datastories with their unique perspective. We are the community that is creating Citizen Data Scientists and we are committed to help you become one of the Top 1% data storytellers.
With Saurabh Moody and Preksha Kaparwan you can start your journey as a Citizen Data Scientist.
All the Best❤️
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