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This project involves a comprehensive analysis of the Frictional Company dataset. By writing and executing targeted SQL queries, I extracted valuable business data, to uncover key trends and patterns. The final output provides actionable recommendations and strategic business insights to drive informed decision-making.

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jiyanshgarg/XYZToyShop-SQLProject

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Business Case - XYZ Toy Shop Ltd

About XYZ Toy Shop Ltd. – Inspiring Joy, Delivering Joy

XYZ Toy Shop is a beloved global brand and one of Mexico’s leading toy retailers. Known for its outstanding selection, innovative offerings, and customer-focused approach, XYZ Toy Shop has become the top choice for families, educators, and toy lovers everywhere. With high-quality products, competitive prices, and an exceptional shopping experience, the company stands out from its competitors, making playtime more magical for kids and adults alike.

Our analysis is based on a comprehensive dataset of 829,262 sales transactions from January 2022 to September 2023, covering 35 carefully curated product lines. Additionally, 1,593 inventory records provide insights into stock management practices. By examining this extensive data, we can uncover valuable trends in XYZ Toy Shop’s operations in Mexico. The findings shed light on key business aspects, including inventory management, pricing strategies, payment methods, store efficiency, and product performance.

Problem Statement

Assuming you are a data analyst/ scientist at XYZ Toy Shops Ltd, you have been assigned the task of analyzing the given dataset to extract valuable insights and provide actionable recommendations.

Dataset

There are 4 tables :-

Tools Used :-

Google BigQuery

Key Findings and Insights

  • Top Performers: Colorbuds (Electronics), PlayDoh Can, Barrel O' Slime, and Deck Of Cards each sold 80,000+ units, demonstrating strong consumer demand for affordable, high-margin items.
  • Underperformers: Playfoam, Chutes & Ladders, Monopoly, Uno, and Mini Basketball Hoop (all <6,000 units) likely suffer from high pricing, market saturation, or niche appeal.
  • Inventory & Supply Chain
    • Forecasting: Drastically increase stock before high-growth months (e.g., November).
    • Liquidation: Implement aggressive markdowns/bundles post-holiday (January) to clear excess inventory.
    • Replenishment: Prioritize and expedite stock for critically low stores (Saltillo 1, Guanajuato 1).
    • Best Practices: Standardize successful inventory strategies from top-performing "Well-Stocked" stores chain-wide.
  • Marketing & Sales
    • Demand Smoothing: Run targeted campaigns during traditional low-growth months (Jan, Feb, Aug).
    • Seasonal Campaigns: Launch "Pre-Holiday" (Oct/Nov) and "Post-Holiday" (Jan) sales events.
    • Localization: Empower store managers with budgets for location-specific promotions.

Query :-

https://console.cloud.google.com/bigquery?sq=678479259304:2f82880f053249af83f372ae3e824c0e

About

This project involves a comprehensive analysis of the Frictional Company dataset. By writing and executing targeted SQL queries, I extracted valuable business data, to uncover key trends and patterns. The final output provides actionable recommendations and strategic business insights to drive informed decision-making.

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