naushadcom / E-Commerce-Sales-Analysis

This project analyzes sales data from a Brazilian e-commerce store (2016-2018) to identify sales trends across states. Objectives include pinpointing states with increasing or declining sales, conducting root cause analysis, and providing recommendations for improvement.

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E-Commerce-Sales-Analysis

Introduction

This project aims to analyze the sales data of a Brazilian e-commerce store from 2016 to 2018. The main objectives are to understand sales trends across different states, identify states with declining or increasing trends, perform a root cause analysis for their performance, and provide recommendations for improvement.

Objectives

Metrics Calculation:

Calculate the following metrics for each year and state: Sales Customer acquisitions Total number of orders Analyze if these metrics show similar trends or disparities.

Trend Identification:

Identify the top 2 states with: Declining trends over the years Increasing trends over the years Use the most suitable metrics among sales, customer acquisitions, and total number of orders for this analysis.

Root Cause Analysis:

Perform a detailed analysis for the identified states using various metrics: Category-level sales and orders placed Post-order reviews Seller performance in terms of deliveries Product-level sales and orders placed Percentage of orders delivered earlier or later than the expected date

City-Level Analysis:

Perform the above analysis for the top 2 cities contributing to the trends in each of the identified states.

Recommendations:

Based on the root cause analysis, suggest ways to improve the performance of the identified states and cities.

Power BI Dashboard

Meaningful Insights

Total Sales and Orders:

The total sales amount to 13.59 million. Total orders are 96K, indicating the average order value is approximately $141.46 (13.59M / 96K).

Customer Acquisition:

The customer acquisition number is 96K, indicating all orders are from unique customers (assuming each acquisition results in a single order). Top Product Categories by Sales:

The top 5 product categories are "Health & Beauty," "Watches," "Bed & Bath," "Sports & Leisure," and "Computers," with sales ranging from 0.91M to 1.26M. This suggests these categories are the most popular and should be prioritized in marketing and inventory planning.

Geographical Distribution of Orders:

The majority of orders (51.89%) come from the state of SP, followed by BA (20.86%) and MG (8.52%). Targeted marketing campaigns in these states could be beneficial.

Payment Methods:

Most transactions (78.34%) are made using credit cards, followed by boleto (17.92%). It's crucial to maintain and perhaps expand credit card and boleto payment options to cater to customer preferences.

Monthly Order Trends:

There is a noticeable peak in orders around October, with a significant drop in December. This suggests a strong sales period during Q4, possibly due to holiday shopping, followed by a post-holiday decline.

Product Category Price Trends:

The price of product categories has fluctuated over the years (2016-2018). Notable increases in the average price of categories like "health and beauty," "houseware," and "watches" in 2017 indicate potential market trends or shifts in consumer preferences.

Sales Trends by State:

SP shows significantly higher total sales compared to other states, indicating it is the most lucrative market. States like ES, PE, and BA show considerably lower sales, suggesting potential areas for growth or increased marketing efforts.

Order Distribution by State:

The state of SP dominates with 51.89% of orders, followed by BA and MG. There is a significant drop-off in orders in other states, which could indicate either market saturation in SP or untapped potential in lesser-performing states.

Payment Method Preferences:

Credit cards are overwhelmingly preferred (78.34%), while other methods like debit cards and vouchers are minimally used. Exploring incentives for using alternative payment methods might diversify payment preferences and potentially increase sales.

Monthly Order Fluctuations:

Orders peak in October and drop sharply in December. This could indicate a strong pre-holiday shopping period, followed by a post-holiday sales slump. Implementing strategies to boost post-holiday sales could help balance this drop.

Top Sales States and Product Categories:

Combining insights from top-selling states and product categories, it's evident that the most popular categories (health and beauty, watches, etc.) should be heavily stocked and promoted in SP, BA, and MG.

Recommendations to Improve Performance:

Enhanced Marketing Campaigns: Tailor promotions to target states and cities with declining trends. Improved Logistics: Optimize delivery routes and reduce fulfillment times. Customer Feedback Loop: Regularly collect and analyze customer feedback to address issues promptly. Product Assortment: Adjust product offerings based on regional preferences and demand. Local Partnerships: Collaborate with local businesses to boost brand presence and customer trust. Data-Driven Decisions: Utilize sales data to make informed decisions about inventory, pricing, and promotions. By implementing these recommendations, the e-commerce store can enhance its performance across different states and cities, leading to increased sales and customer satisfaction.

About

This project analyzes sales data from a Brazilian e-commerce store (2016-2018) to identify sales trends across states. Objectives include pinpointing states with increasing or declining sales, conducting root cause analysis, and providing recommendations for improvement.


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