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Make your own version of Olist Marketplace Insights

Edit the prompt below and generate a customized version in seconds.

Original by sunkavya10

Describe your app

Build a complete, professional Olist E-Commerce Data Analytics project using the 9 provided CSV datasets.

Analyze marketplace performance, customer satisfaction, delivery, sellers, geography, products, categories, and payments.

Include:
• Data loading, cleaning, missing-value handling and duplicate checks
• Correct joins between all datasets
• Monthly order, revenue and review-score trends
• Total revenue, orders, AOV and growth KPIs
• Delivery time, delivery delay and on-time/late delivery analysis
• Relationship between delivery performance and review scores
• Seller performance and seller-state analysis
• Customer geography and state-wise performance
• Product/category orders, revenue, price, freight and review analysis
• Payment-type and installment behavior analysis
• Repeat-customer analysis using customer_unique_id
• Freight cost vs product weight/dimensions analysis
• Seller-to-customer geographic analysis where possible
• Low-review root-cause analysis
• Optional review-text sentiment and anomaly analysis

Create an interactive dashboard with:
1. Executive Overview
2. Delivery & Customer Satisfaction
3. Seller & Geography
4. Product Category Performance
5. Payment Analysis
6. Root Cause Analysis

Add KPI cards, filters, line charts, bar charts, scatter plots, heatmaps, maps and rankings.

Focus on the 6 core questions from the problem statement. Generate evidence-based insights, identify primary and secondary factors affecting customer satisfaction, and provide actionable business recommendations.

Important:
• Use actual uploaded data only.
• Do not fabricate results.
• Avoid duplicate rows after joins.
• Aggregate payments/items correctly at order level.
• Aggregate geolocation before joining.
• Use customer_unique_id for repeat-customer analysis.
• Handle missing delivery timestamps appropriately.
• Do not claim correlation as causation.

Final output must include the cleaned data/model, EDA, KPI analysis, interactive dashboard, key findings, root-cause analysis, business recommendations, executive summary, and a concise “Key Business Story” suitable for a hackathon presentation.

Free to use. No credit card required.