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📘This repository provides a detailed exploration of Walmart's BlackFridaySales data using the Central Limit Theorem (CLT) coupled with Confidence Interval Analysis. Leveraging statistical techniques, we delve into the nuances of customer behavior, purchase patterns during one of the busiest shopping events of the year.

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boxcox matplotlib-pyplot numpy-library pandas-library python3 scipy-stats seaborn statsmodels stats-norm

walmart-blackfridaysale-casestudy's Introduction

🧺✴️Walmart - Business CaseStudy✴️🧺

[CLT and Confidence Interval]

WalmartCanada-Storefront

WalmartLogoGIF

🧺WALMART :

Walmart, founded in 1962 by Sam Walton, is a retail giant and one of the world's largest and most influential companies. Headquartered in Bentonville, Arkansas, this American multinational corporation has established itself as a global powerhouse in the retail industry. Walmart operates a vast network of hypermarkets, discount department stores, and grocery stores under various brand names across the United States and in numerous countries around the world.

Known for its "Everyday Low Prices" strategy, Walmart has redefined the retail landscape with its commitment to offering a wide range of products at affordable prices. With its extensive supply chain and efficient distribution systems, the company has played a pivotal role in shaping consumer expectations and shopping habits. Beyond retail, Walmart has also ventured into e-commerce, technology innovation, and sustainability initiatives, further solidifying its position as a key player in the modern retail ecosystem.

  • Walmart: Where Shopping Becomes a Global Phenomenon

Walmart, the retail titan, stretches its tentacles across 19 countries, boasting over 10,500 stores and serving more than 100 million customers worldwide. It's not just a shopping haven; it's a data goldmine waiting to be unearthed.

  • A Retail Colossus with a Human Touch

Despite its vast size, Walmart remains dedicated to its core values of customer service and community involvement. The company's philanthropic efforts focus on areas like hunger relief and children's health, and its commitment to employee development has earned it recognition as a top employer.

Walmart's story is far from over. As the retail landscape continues to evolve, this retail giant is sure to adapt and innovate, remaining a dominant force in the world of shopping.

Business Problem:

🏷️ Objective

  • The Management team at Walmart Inc. wants to analyze the customer purchase behavior (specifically, purchase amount) against the customer’s gender and the various other factors to help the business make better decisions.
  • They want to understand if the spending habits differ between male and female customers: Do women spend more on Black Friday than men? (Assume 50 million customers are male and 50 million are female).

📝 Case Report

  • You can access the complete Case python file here - Python
  • You can access the complete Casestudy in pdf format here - Report

👀 About Data

The company collected the transactional data of customers who purchased products from the Walmart Stores during Black Friday.

📃 Features of the dataset:

The dataset has the following features:

Feature Description
User_ID User ID
Product_ID Product ID
Gender Sex of User
Age Age in bins
Occupation Occupation(Masked)
City_Category Category of the City (A,B,C)
StayInCurrentCityYears Number of years stay in current city
Marital_Status Marital Status
ProductCategory Product Category (Masked)
Purchase Purchase Amount

Outcome:

🧺Leveraging Conclusions for WALMART🧺:

  • ❇️Targeted Marketing

    🔹Boost spending for 0 - 17 age group with attractive incentives and tailored marketing.

  • ❇️Customer Segmentation

    🔹Optimize product selection and pricing for age groups with similar buying behaviors.

  • ❇️Premium Services

    🔹Enhance the shopping experience for high-spending 51 - 55 age group with premium services and tailored loyalty programs.

  • ❇️Identifying Differences:

    🔹Walmart can capitalize on the recognized distinctions between male and female customer behaviors.

    🔹Tailoring marketing strategies, product offerings, and promotions based on these differences can enhance customer engagement.

    🔹By understanding gender-specific preferences, Walmart can create more targeted and appealing campaigns for each demographic.

  • ❇️Decision-Making:

    🔹Decision-makers at Walmart now have valuable insights to inform their strategic decisions.

    🔹Understanding how gender influences customer choices enables more precise decision-making in areas such as product assortment, pricing strategies, and promotional activities.

    🔹Informed decision-making ensures that resources are allocated effectively, maximizing the impact of business initiatives.

  • ❇️Operational Adjustments:

    🔹Operational aspects, such as inventory management and store layout, can benefit from insights into gender-related patterns.

    🔹Walmart may consider optimizing inventory based on observed preferences, ensuring that popular products are well-stocked.

    🔹Store layouts can be adjusted to enhance the shopping experience for both genders, creating a more personalized and enjoyable atmosphere.

In summary, leveraging these conclusions empowers WALMART to tailor its approach to different customer segments, make informed decisions grounded in observed behaviors, and optimize operational aspects for a more customer-centric and efficient retail experience. WALMART can strategically implement changes to drive customer engagement, increase sales, and enhance the overall shopping experience.


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