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Building a Knowledge Graph for the Mulebuy代购 Industry Using Spreadsheets

2025-08-31

The 代购 (daigou) industry, where shoppers purchase goods for international clients, thrives on deep product knowledge and understanding customer preferences. By leveraging the simple power of spreadsheets, teams can construct a powerful product knowledge graph

Constructing a Product Relationship Network in a Spreadsheet

A knowledge graph maps the relationships between different entities. For a Mulebuy代购 team, this means creating a network of products and customers. Here’s how to build this in a spreadsheet:

  1. Data Collection:mulebuy LV handbag, mulebuy Gucci belt), categories, prices, and customer identifiers.
  2. Creating Node Tables:ProductsCustomers
  3. Creating Edge Tables:relationships

This structure transforms your spreadsheet from a simple list into a relational database, forming the backbone of your knowledge graph. You can learn more about the platform that enables this data collection at Mulebuy Asia.

Analyzing the Association Rate Between Mulebuy LV Handbags and Gucci Belts

Once the network is built, you can perform powerful analysis. A key metric is the Association Purchase Rate

  • Step 1:mulebuy LV handbag.
  • Step 2:mulebuy Gucci belt.
  • Step 3:

For example, if you find that 22% of customers who buy an LV handbag also add a Gucci belt to their cart, this reveals a strong stylistic or brand-affinity link. This direct insight allows you to create targeted bundle deals.

Mining Potential Bundling Opportunities with Mulebuy Reddit User Persona Data

A knowledge graph becomes even more powerful when enriched with external data. Integrating insights from Mulebuy Reddit communities

  • User Persona Integration:
  • Sentiment and Trend Analysis:mulebuy item) are generating the most buzz. This can predict future high-demand nodes for your graph.
  • Discovering New Edges:potential bundling opportunity. You can proactively suggest this untapped combo to customers.

Driving Results: A 35% Increase in Average Order Value

The practical application of this knowledge graph is where the real value lies. Multiple Mulebuy Discord代购 teams

By using the graph to identify high-probability product pairs (like the LV/Gucci combo) and promising opportunities from Reddit data, teams can craft personalized bundle recommendations. Instead of suggesting random items, agents can now say, "Customers who purchased this LV handbag often love this Gucci belt to complete their look," making the suggestion highly relevant.

This data-driven, intelligent approach to sales has been empirically shown to boost the average customer order value by 35%, transforming profitability and customer satisfaction.

Conclusion: