Building User Profile Data in Spreadsheets for E-Commerce and Shopping Agent Platforms and Its Application in Precision Marketing-ACBuy spreadsheet-The best and new spreadsheet

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In the era of big data, integrating and analyzing user information from multiple e-commerce platforms and shopping agent websites has become a crucial strategy for precision marketing. This article presents a methodology for constructing comprehensive user profiles using spreadsheet tools (such as Google Sheets or Excel) and applying them to enhance marketing effectiveness.

1. Data Collection and Integration in Spreadsheets

The first step involves aggregating user data from various sources into structured spreadsheets:

Basic Information:
Transaction Data:
Behavioral Data:
Preference Indicators:
Social Data:

Spreadsheet formulas and scripts can be used to clean and normalize this multi-source data into a unified format.

2. User Profile Modeling Techniques

With spreadsheet-based data prepared, we implement various analytical techniques:

2.1 Data Mining Approaches

RFM (Recency, Frequency, Monetary) customer segmentation

Cluster analysis for behavioral grouping

2.2 Spreadsheet-Compatible ML Techniques

Using spreadsheet script languages to implement:

Potential value scoring models

Churn prediction algorithms

Personalized recommendation engines

Applied Case: A hybrid algorithm of:

purchase frequency score (30%) + average order value (30%) + product category preference (20%) + responsiveness to marketing (20%)

3. Multi-Dimensional User Tagging System

Dimension Tag Examples

Demographics 25-30F_Urban_Premium

Behavioral Night_Buyer_Impulsive

Preference Skincare_Enthusiast_LuxuryBrands

Value HighARPU_Loyal

This multidimensional labeling creates complete 360° customer profiles directly in spreadsheet format.

4. Precision Marketing Applications

4.1 Targeted Campaigns

Use FILTERQUERY
4.2 Dynamic Content Personalization Automate content variations based on user clusters Implementation Case Study Regarding Metrics Improvement: 38% increase in email open rates 2.7X improvement in conversion from recommendations 170% ROI on remarketing campaigns
Data-Driven Marketing Future By utilizing spreadsheet platforms as the central hub for integrated user data and machine-learning-powered analysis functions, e-commerce platforms and shopping agent sites can achieve previously unattainable levels of marketing precision and effectiveness. Future enhancement possibilities include real-time data processing pipelines and API-based marketing automation testing directly from spreadsheet environments. ```

Dimension	Tag Examples
Demographics	25-30F_Urban_Premium
Behavioral	Night_Buyer_Impulsive
Preference	Skincare_Enthusiast_LuxuryBrands
Value	HighARPU_Loyal