🚲 Business Performance Analysis & Strategic Recommendations | PART 2
- Matias Rossi
- Mar 24
- 4 min read
Bike Retail Company | 2016 - 2018 | Data Analysis Report
📌 Executive Summary
This report presents a data-driven business analysis of a bike retail company with three U.S. stores, using SQL for data extraction, Looker Studio for visualization, and strategic analysis to derive actionable insights.
Following a structured data analytics approach, I first queried the database using SQL to explore trends, then visualized key findings in Looker Studio, and finally interpreted the results to provide business recommendations.
The analysis uncovered strong revenue performance in 2016 and 2017, followed by a steep decline in 2018, signaling operational and market challenges. Additionally, customer retention is critically low—with over 90% of buyers purchasing only once—and store performance varies dramatically, with one store dominating sales (65%) while another contributes only 10%.
To address these challenges, this report outlines strategic recommendations, including loyalty programs, store optimization, and inventory management improvements, to help the company enhance profitability and long-term sustainability.
📊 Key Findings & Business Insights
1️⃣ Revenue & Order Trends
✔ Strong Sales in 2016 & 2017 – Clear seasonal demand spikes in Q3 & Q4, aligning with peak cycling seasons.
✔ Revenue Collapse in 2018 – Orders dropped sharply after an April revenue spike ($909K, 125 orders), followed by a sustained decline.
✔ Potential Root Causes – Possible store closures, supply chain disruptions, or external competition need further investigation.
🔎 Business Impact: The company is experiencing a severe loss in revenue, requiring urgent intervention to stabilize operations.
2️⃣ Customer Retention Issues
✔ Only 9% of customers placed more than one order, meaning 91% are one-time buyers.
✔ This suggests poor retention & lack of customer loyalty strategies.
✔ No existing engagement mechanisms (e.g., discounts for repeat buyers, personalized offers).
🔎 Business Impact: The company is missing out on repeat business and long-term customer value, significantly reducing revenue potential.
3️⃣ Store Performance Disparities
✔ Baldwin Bikes (NY) dominates sales (65% of total revenue).
✔ Santa Cruz (CA) contributes 20%, while Rowlett (TX) underperforms at 10%.
✔ Underperforming stores may need operational improvements, location analysis, or revised marketing efforts.
🔎 Business Impact: Sales concentration in one store poses a business risk, while underperforming locations require optimization or resource reallocation.
4️⃣ Product Category Insights
✔ Mountain Bikes – Best-selling category, highest total revenue.
✔ Road Bikes – Lower volume but high per-unit profitability.
✔ Electric Bikes – High revenue per unit but low sales volume, possibly due to pricing barriers.
✔ Children’s & Comfort Bikes – Underperforming, requiring reassessment of demand & marketing strategy.
🔎 Business Impact: The company is generating most of its revenue from select high-margin products, requiring an inventory and sales strategy adjustment.
5️⃣ Operational & Inventory Considerations
✔ Drastic Sales Decline Post-April 2018 suggests possible inventory shortages or fulfillment issues.
✔ Order status inconsistencies require investigation into cancellations & delivery delays.
🔎 Business Impact: Inefficient stock management and fulfillment processes could be causing revenue loss and customer dissatisfaction.
📈 Data-Driven Strategic Recommendations
📌 1️⃣ Investigate the 2018 Sales Collapse
✔ Conduct internal audits to determine if store closures, supply chain failures, or external competition were responsible.
✔ Customer feedback analysis to assess whether service quality issues contributed to the decline.
📌 2️⃣ Enhance Customer Retention & Loyalty
✔ Implement a loyalty rewards program to incentivize repeat purchases.
✔ Launch personalized email campaigns targeting past customers with exclusive offers.
✔ Introduce subscription-based services (e.g., maintenance plans, early product access) to build long-term engagement.
📌 3️⃣ Optimize Store Performance & Expansion Strategy
✔ Reassess underperforming stores – Conduct a market potential study for Santa Cruz & Rowlett.
✔ Retrain staff, optimize store layout, and strengthen local marketing efforts.
✔ Consider reallocating inventory and resources to match demand more effectively.
📌 4️⃣ Focus on High-Margin & High-Demand Products
✔ Promote Road & Electric Bikes, as they yield higher per-unit revenue.
✔ Reevaluate Children’s & Comfort Bikes – Conduct market research before further inventory investment.
📌 5️⃣ Improve Operational Efficiency & Inventory Management
✔ Optimize stock levels to prevent overstocking/shortages of high-demand products.
✔ Audit order fulfillment to minimize cancellations and reduce delivery delays.
✔ Automate demand forecasting to align stock levels with seasonal trends.
📌 Conclusion & Personal Insights
This SQL-powered business analysis provided valuable insights into revenue trends, customer behavior, store performance, and product profitability. The findings highlight a clear need for strategic action, particularly in customer retention, store optimization, and inventory management.
By implementing the data-driven recommendations outlined, the company can:
✅ Recover lost revenue and prevent future declines.
✅ Increase customer loyalty and repeat purchases.
✅ Optimize store performance and resource allocation.
✅ Maximize profitability by focusing on high-margin products.
🌟 My Experience with This Project
This was my first end-to-end SQL project focused on extracting actionable business insights, and it reinforced my confidence in SQL as an essential tool for decision-making.
At first, SQL seemed like just another technical skill, but now I clearly see its power in transforming raw data into strategic insights. The ability to answer key business questions in seconds and provide stakeholders with accurate, real-time information is invaluable.
This project also strengthened my belief that cloud-based analytics is the future—allowing businesses to store, visualize, and act on data efficiently.
🚀 What’s Next? I will continue refining my Business Intelligence skills, applying these insights to real-world data problems, and improving my ability to turn data into strategy. More projects to come! (Maybe some insights of my own business management?)
🔗 Additional Resources
📂 Full SQL Code & Analysis: GitHub Repository
📊 Dataset Used: Bike Retailer Dataset
💼 Connect with Me: LinkedIn Profile
🚀 For business inquiries or further insights, feel free to reach out!
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