In today’s competitive e-commerce landscape, data-driven decision-making is critical for optimizing sales strategies and enhancing customer experience. TrendyTech, an online retailer specializing in electronics and accessories, faced challenges in understanding customer behavior, product performance, and marketing effectiveness. This case study explores how data analytics can help improve revenue and reduce cart abandonment.

Business Challenges

TrendyTech’s marketing team suspected inefficiencies in their current sales strategy but lacked the necessary insights. The key challenges included:

  1. Sales Performance Issues – Identifying best-selling and underperforming products.
  2. Customer Behavior Analysis – Understanding purchasing patterns and user engagement.
  3. Marketing Impact Evaluation – Measuring ROI from campaigns and promotions.
  4. Cart Abandonment Analysis – Addressing lost sales opportunities and optimizing conversions.

Step-by-Step Data Analysis Approach

1. Sales Performance Analysis

Key Metrics:

  • Total Sales Revenue
  • Best-Selling Products & Categories
  • Seasonal Trends in Sales

Implementation:

  • Google Sheets/SQL: Extract transactional data and apply SUM() for revenue calculations.
  • Power BI: Visualize sales trends using bar charts and line graphs.

2. Customer Behavior Insights

Key Metrics:

  • Average Order Value (AOV)
  • Repeat Customer Rate
  • Customer Segmentation (New vs. Returning Buyers)

Implementation:

  • SQL Queries: Use GROUP BY to analyze purchase frequency.
  • Power BI: Create customer segmentation heatmaps.

3. Marketing Effectiveness Evaluation

Key Metrics:

  • Conversion Rate per Campaign
  • Cost Per Acquisition (CPA)
  • Customer Lifetime Value (CLV)

Implementation:

  • Google Sheets: Track marketing spend vs. revenue.
  • Power BI: Compare campaign performance with funnel visualizations.

4. Cart Abandonment Analysis

Key Metrics:

  • Cart Abandonment Rate
  • Drop-off Points in the Purchase Funnel
  • Time Spent Before Abandonment

Implementation:

  • SQL Queries: Use LEFT JOIN to compare initiated and completed purchases.
  • Power BI: Create funnel charts for abandonment trends.

Deliverables

  1. Interactive Dashboard – Built in Power BI or Google Sheets.
  2. Insights Report – A short presentation summarizing findings.
  3. SQL Queries – To retrieve and analyze data efficiently.

Key Business Insights & Recommendations

  1. Optimize Product Pricing – Adjust pricing based on best-seller trends.
  2. Enhance Retargeting Strategies – Implement targeted campaigns for abandoned carts.
  3. Improve UX for Checkout Process – Reduce friction in the final purchase stage.
  4. Invest in High-Performing Marketing Channels – Allocate budgets to campaigns with the best ROI.

Final Thoughts

By leveraging Power BI, SQL, and Google Sheets, TrendyTech can make data-driven decisions to improve sales, optimize marketing efforts, and enhance customer retention. Implementing a structured data analysis framework allows e-commerce businesses to stay ahead in a competitive market.

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