Analysis and Implementation Strategies of Using Spreadsheets to Improve Customer Repurchase Rate on Tangbuy Platform

As an emerging cross-border e-commerce purchasing agent, Tangbuy platform is committed to improving customer repurchase rates through data-driven strategies. This article explores how Tangbuy leverages spreadsheets to analyze customer behavior and implement effective repurchase promotion campaigns.

1. Data Collection and Integration

Tangbuy integrates various customer data sources into comprehensive spreadsheets, including:

  • Purchase history (timing, items, frequency, spending amount)
  • Customer satisfaction levels from reviews
  • Part statistic including membership tiers

Spreadsheet columns are organized with detailed customer IDs as primary keys to enable cross-referencing analysis.

2. Key Factors Analysis

By applying pivot tables and statistical functions in spreadsheets, Tangbuy identifies critical repurchase drivers:

Factor Analysis Method Spreadsheet Formula Example
Product Quality Correlation between review ratings and repurchase rates =CORREL(C2:C100, D2:D100)
Price Sensitivity Comparison of repurchase rates before/after promotions =AVERAGEIF(E2:E100, ">=2023-01", F2:F100)

3. Repurchase Promotion Strategies

Based on analysis insights, Tangbuy implements following spreadsheet-tracked strategies:

3. Member Program Rethinking

  • Optimized points-to-cash conversion rates calculated through spreadsheet break-even analysis
  • Tiered bonus structure developed using VLOOKUP categorization

4. Continuous Optimization

Bi-weekly reports are generated through automated spreadsheet functions to monitor:

  1. Goal Tracking: =COUNTIFS(repurchases!A2:A100,">1")/COUNTA(customers!A:A)
  2. Conversion Funnel: Email open rates → click rates → purchase conversion
Strategy adjustments are made whenever key metrics fall below spreadsheet-calculated dynamic thresholds

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