Brief

This workflow automates product-based searches on a B2B e-commerce marketplace and extracts key details from multiple seller listings on the results page. It captures essential information such as product name, price, minimum order quantity, seller verification status, and years of operation, enabling quick comparison of different wholesalers for sourcing and market analysis.

Future Integration Possibilities

This workflow can be extended by integrating with automation platforms such as Make or n8n. The extracted product listing data can be passed into automated rules and filters to match specific e-commerce requirements, such as target price range, minimum order quantity, verified sellers only, or supplier experience. Based on these rules, the workflow can automatically shortlist suitable products, store results in databases or spreadsheets, and trigger alerts or follow-up actions for e-commerce owners and sourcing teams.

What does this workflow do?

This workflow automates the process of searching for products across B2B marketplaces and extracting essential listing details from multiple sellers. It collects key information such as product name, price, minimum order quantity, seller verification status, and years of operation.

From a business perspective, this workflow enables e-commerce owners and sourcing managers to quickly compare suppliers, identify verified and reliable sellers, and make data-driven purchasing decisions. By saving time and reducing manual effort, it enhances operational efficiency and supports strategic sourcing.

Additionally, the workflow can be integrated with automation platforms like Make or n8n, allowing businesses to set custom rules and filters. For example, only products meeting predefined criteria—such as price range, MOQ, or verified seller status—can be automatically collected and forwarded for further processing. This makes it a scalable and intelligent tool for e-commerce decision-making and inventory planning.

What data can you scrape from Alibaba ?

The workflow collects key details from multiple product listings, including:

Product Name – the title of the product as listed.
Product URL – the direct link to the product page.
Price – listed price or price range.
Minimum Order Quantity (MOQ) – the smallest quantity a seller accepts.
Seller Verification Status – whether the seller is verified or unverified.
Years of Operation – how long the seller has been active (if displayed).

This data allows users to compare products and suppliers, make data-driven sourcing decisions, and efficiently analyze e-commerce opportunities.

How to use this workflow ?

Open the workflow.
Set the two parameters here:
- target_url – the marketplace URL to extract data from.
- target_product – the product name you want to search and extract.
Change the target_product according to your own need.
Click the Start button to begin the workflow.
The workflow automatically searches for the product, collects listing details from multiple sellers, and saves the results in a CSV file.
You can also adjust the loop iteration.
The extracted data can be used to compare suppliers, analyze prices, and make informed sourcing decisions.

Why scrape Alibaba ?

Access to multiple suppliers: Alibaba hosts thousands of manufacturers and wholesalers, allowing users to compare options quickly.
Save time and effort: Manual searching for product and supplier details is slow and inefficient; automation speeds up the process.
Data-driven sourcing decisions: Extracting structured information like price, MOQ, seller verification, and years of operation enables smarter purchasing.
Competitive advantage: Businesses can identify the best suppliers and pricing, helping to optimize inventory and margins.
Scalability: Automating the process allows repeated searches for multiple products without extra manual work.

140-200credits per task (estimated)