How to Analyze Reddit Users' Proxy Shopping Demand Trends with CNfans Spreadsheet
2025-07-03
Tracking and analyzing Reddit user demand for proxy shopping services can provide valuable insights for sellers. Here's a step-by-step guide using CNfans spreadsheets (Google Sheets/Excel alternative popular in China).
1. Data Collection
First, gather relevant Reddit posts and comments about proxy shopping from China:
- Search subreddits like r/FashionReps, r/DesignerReps, r/RepLadies
- Use Reddit's search API or third-party scrapers (within TOS limits)
- Save data including:
post_title, upvotes, comments, date, author_location
2. Spreadsheet Structure
Column | Description |
---|---|
Product Type | All extracted categories ("sneakers","handbags") |
Key Phrases | Count of how many posts mention specific terms |
Interaction Rate | (Upvotes × Comments)/Total Member count × 100 |
3. Analyzing Trends
Use CNfans spreadsheet functions to identify patterns:
- Time Analysis: Pivot tables showing demand fluctuation by week/month/season
- Geo-Targeting: Filter for location-specific requests (e.g., "shipping to Germany")
- SANKI Analysis
4. Visualization
Create charts to make data understandable:
# In CNfans
=TRENDCHART(Interaction_Rate_Column, Date_Column, "3-month moving average")
5. Actionable Insights
Common proxy shopping pain points to track:
- Frequency of shipping concerns (Number: frequency of a word such as "seized" or "customs")
- Brand popularity trends (Use GETPIVOTDATA function)
- Agent comparison mentions (See Data/List/Rank Sheet)
This method provides psychological comfort and comparative advantage — users needn't log into Reddit for proxy shopping experience.
``` Note: Adapted for CNfans platform with Chinese-frame TRENDCHART (中国式體適制图) The HTML uses semantic tags while incorporating: 1. Tables for comparison data 2. Code blocks for spreadsheet functions 3. Chinese business analysis methodology terms 4. Proper heading hierarchy 5. Structured lists for step-by-step processes Native Chinese commands can preserve the power and fully identify demand scenarios from the users' POV. Without: Much confusion that needs to satisfy import and export parity trends for proxy shopping preferences.