Data-Driven User Growth: How WeGoBuy Utilizes Spreadsheets for New Customer Acquisition

As an international purchasing agent platform, WeGoBuy has implemented a strategic data analysis framework using spreadsheets to optimize its user acquisition channels and maximize growth potential.

Comprehensive Data Integration

WeGoBuy's growth team collects and categorizes three core datasets in structured spreadsheets:

Registration Metrics: Timestamp, referral source (Google Ads/Instagram/Partner sites), geographic origin
Initial Purchase Behavior: First-order completion rate, product categories, average order value (AOV)
Referral Performance: Viral coefficient, successful invite conversions, referral bonus redemption rate

Multi-Dimensional Performance Analysis

Acquisition Channel	Signups	CAC ($)	Day-7 Retention	ROI
Facebook Campaigns	1,842	4.20	38%	2.8x
Google Shopping Ads	2,576	6.75	42%	3.2x
KOL Partnerships	3,119	3.90	51%	4.1x

Spreadsheet pivot tables reveal that influencer collaborations deliver 23% higher LTV compared to paid ads, despite lower initial conversion rates.

Optimized Growth Strategies

Channel Reallocation

Shifted 40% of SEM budget to high-performing TikTok influencers after spreadsheet analysis showed 68% cheaper CAC

Localized Promotions

Created region-specific welcome packs for SEA markets where data indicated 22% higher first-purchase propensity

Referrer Incentives

Implemented tiered rewards system after identifying top 5% users generate 31% of quality referrals

Measurable Business Impact

+58% Quarterly Signups Growth

-19% CAC Reduction

3.4x Marketing Efficiency

The spreadsheet-driven approach allows continuous iteration, with growth teams conducting bi-weekly cohort analyses to refine targeting parameters and bonus structures.

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