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:

  1. Time Analysis: Pivot tables showing demand fluctuation by week/month/season
  2. Geo-Targeting: Filter for location-specific requests (e.g., "shipping to Germany")
  3. 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)
<Action Commands>

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.

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