Automated Campaign Execution
The integrated system triggers marketing actions when specific user threshold conditions
Early implementations show 18-35% improvement
Building E-commerce and Shopping Agent Platform User Profiles in Spreadsheets for Precision Marketing Applications
2025-04-27
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Introduction
In the digital commerce era, integrating user data from multiple e-commerce platforms and shopping agent websites into spreadsheet applications
Data Collection Framework
Multi-Source Data Aggregation
Our spreadsheet-based system collects three primary data categories from e-marketplaces (Amazon, eBay, Taobao)shopping agent platforms (Superbuy, Bhiner):
- Demographics: Age, location, gender, income level
- Transaction Records: Purchase history, frequency, product categories
- Behavioral Signals: Click patterns, browsing duration, wishlist items
The import/sync functions enable real-time data updates through platform APIs and web scraping tools configured directly within the spreadsheet environment.
User Profile Modeling Techniques
Data Mining Algorithms Implementation
Using spreadsheet-embedded script functions (Google Apps Script/Python macros), we implement:
RFM analysis- Purchase pattern
cluster analysis- Natural language processing of
product review sentiment- Purchase pattern
| User ID | Value Segment | Category Preference | Price Sensitivity |
|---|---|---|---|
| U10042 | High-value repeat | Electronics | Low (Premium focus) |
Precision Marketing Applications
Implementation Case Example
A beauty brand using this approach archived:
Conclusion
This spreadsheet-centric solution democratizes big consumer analytics for small/medium merchants, providing:
Cost-effective alternative to enterprise CDP systems
Flexible integration with existing marketing workflows
Visual data exploration through conditional formatting/native charts