Project Overview
This project uses data-driven insights to support Amazon’s customer – centric philosophy by analysing pricing ranges, discounting transparency, product range and customer ratings. The scope involves assessing product feedback, price transparency, and brand variety to determine drivers of satisfaction and potential area for improvement. It uncovers what truly drives customer satisfaction and where Amazon can still improve. Focusing on the Indian market with some dataset limitations, the analysis aims to reveal actionable for improving customer satisfaction, driving loyalty, and sustaining Amazon's competitive advantage amidst the dynamic e-commerce landscape.
Business Objectives
Amazon’s commitment to data-driven decision-making extends far beyond routine operations. The company actively leverages customer feedback, reviews, and behavioural data to refine its offerings and enhance the overall shopping experience.
The primary objective of this project is to leverage data-driven analysis to support Amazon’s customer-centric philosophy.
Specifically, the analysis aims to:
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Understand the top selling brands and therefore top selling categories
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Analyse product variety across categories to identify gaps and opportunities
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Study customer ratings and feedback to uncover satisfaction drivers and areas (products) needing improvement
By addressing these focus areas, the goal is to generate actionable insights that help enhance customer satisfaction, encourage loyalty, and align with Amazon’s core value of delivering a superior shopping experience.
Scope of Analysis
This project supports Amazon’s customer-centric philosophy by analyzing key factors that influence customer satisfaction and loyalty.
The scope includes:
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Evaluating product ratings and customer feedback
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Identifying patterns in pricing transparency and discount strategies
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Assessing the variety of products across different categories
These elements are central to Amazon’s approach to delivering a personalized and value-driven shopping experience.
By uncovering trends in these areas, the project aims to generate insights that can guide improvements in customer engagement and retention.
Key Stakeholders
1. Customers
Customers are central to this project. Insights will help improve pricing transparency, product variety, and personalized experiences—ultimately enhancing satisfaction and loyalty, which are core to Amazon’s customer-centric philosophy.
2. Marketing & Analytics Team
The marketing and analytics teams will use findings to make data-backed decisions that improve engagement, boost conversion, align offerings with evolving customer preferences, optimize discount strategies and target customers more effectively.
Key Requirements
This analysis requires structured data related to:
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Product ratings and reviews
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Pricing information (including discount patterns)
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Product categories and subcategories
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Brand-wise availability and performance
These data points are essential to identify trends, evaluate customer satisfaction drivers, and support insights aligned with Amazon’s customer-centric goals.
Analytical Questions
This analysis seeks to answer the following business-relevant questions:
1. What are the top 5 brands that generate highest sales and how is the sales volume distributed among them?
(Identify top-performing brands by sales volume and understand how revenue is split among them)
2. What are the satisfaction levels across top-performing brands based on customer ratings?
(Analyse rating distribution to assess how customers perceive each brand)
3. How many unique brands are available in each category?
(Evaluate category diversity by measuring brand availability and presence)
4. What is the range of customer ratings for products in each category?
(Assess product quality variation across categories through min–max rating comparisons)
5. How does the discount percentage relate to customer ratings?
(Analyse whether deeper discounts are associated with higher or lower customer satisfaction)
Desired Outputs
The desired outputs focus on understanding product ratings, variety, and pricing to identify areas for improvement and enhance customer satisfaction.
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Identification of products with repeatedly low ratings, along with key patterns in customer feedback
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Actionable solutions to the issues enhances satisfaction for under-performing products
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Analysis of product and brand variety across categories
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Assessment of price points to determine affordability, competitiveness, and consumer appeal
Limitations & Assupmtions
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Absence of time and location data restricts deeper trend and regional insights.
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However, through supplementary research, it is assumed the data pertains to recent years (within the last 2-3 years) and covers the Indian market.
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Dataset completeness may be affected due to its public source, with possible missing or inconsistent records.
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Employee perspectives and internal company data are not included, limiting stakeholder viewpoints to customer-facing aspects only.
Success Metrics
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Potential to improve average product ratings by 0.2 points for underperforming products.
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Estimated 10% increase in customer satisfaction based on review sentiment and pricing transparency analysis.
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Identification of opportunities to expand product and brand variety, recommending at least 5 new categories or brands.
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Demonstrated ability to provide actionable insights that could be adopted by marketing/product teams.