Research on User Profile Data Construction in Spreadsheets and Precision Marketing Applications for E-Commerce Platforms and Buying Agents-Mulebuy spreadsheet-The best and new spreadsheet

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Introduction

With the rapid growth of e-commerce and cross-border purchasing services, effectively analyzing and utilizing user data has become crucial for businesses. This study explores the methodology of integrating user data from major e-commerce platforms and buying agent websites into spreadsheets to build comprehensive user profiles, which can then be applied in precision marketing strategies such as personalized recommendations and targeted advertising.

Data Collection and Integration in Spreadsheets

Data Sources:basic informationconsumption behaviorinterest preferences
Spreadsheet Organization:Google Apps ScriptPower Query

Building User Profiles via Data Mining and Machine Learning

Preprocessing:
Algorithm Application:Google Sheets' Simple MLPython embeddings.

Label Generation:

Precision Marketing Applications

Case Study: Personalized Recommendations

Example: Users tagged as "Frequent Tech Buyers" receive promotions on new gadgets via email campaigns auto-generated from spreadsheet-linked tools (e.g., Mailchimp).

Case Study: Targeted Ads

Iterate ad content (e.g., Facebook ads) by uploading segmented audience lists from spreadsheets, reducing CPA

Conclusion

Integrating fragmented user data into spreadsheets enables efficient profile modeling and actionable marketing insights. Future work may explore real-time profile updates via cloud-based spreadsheet dashboards.

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