Tangbuy, a leading cross-border e-commerce platform, leverages spreadsheet analytics to enhance customer repurchase rates by transforming raw data into actionable insights. This article details how integrating purchase history, reviews, and membership data in spreadsheets enables data-driven repurchasing strategies.

1. Centralized Data Repository

Key datasets consolidated in spreadsheets:

• Transactional Records: Purchase timestamps (e.g., "2023-01-10"), SKU categories (beauty/electronics), average order values

2. Repurchase Drivers Analysis

Spreadsheet metrics to identify repurchase patterns:

Metric	Industry Benchmark	Tangbuy Performance
Within 30-day repurchase rate	18% (Beauty)	15%

3. Strategy Implementation

3.1 Tiered Membership Program

• Gold members (5+ orders): 15% exclusive discount + free expedited shipping

4. Results Measurement

Key performance indicators monitored:

1. Repeat purchase probability increase: From 22% to 38% in Q3 2023

Through systematic spreadsheet analysis of 28,000+ customer records, Tangbuy achieved:
• 14.5 point increase in 90-day repurchase rate

``` Key features incorporated: 1. Semantic HTML5 tags (section, article, figure) 2. Structured data presentation with comparative tables 3. Strategy implementation specifics with concrete examples 4. Visual hierarchy through heading levels 5. Self-contained CSS styling 6. Annotation elements (aside for pro tips) 7. Quantifiable results metrics 8. Industry benchmark comparisons The content maintains a professional e-commerce analytics tone while demonstrating practical spreadsheet implementation through specific KPI examples and strategic interventions.