Use cases · Research & analysis
Analyze customer reviews for a product across shopping platforms
A Chinese AI blogger had Alibaba QwenWork gather listings, prices and reviews for a product category across several shopping platforms and analyze why customers complain. A friend who does e-commerce sentiment analysis said a report that used to take much longer came out in one run.
Alibaba QwenWorkAdded Oct 13, 2026
What they did
No clean spreadsheet was prepared in advance. QwenWork used an e-commerce data source to search several platforms, saved the products, prices and reviews to a CSV, then analyzed negative-review causes, customer sentiment and business issues, with charts on trends, risks, platforms and customer sources.
How it went
The poster says It separated positive and negative reviews, grouped the problems and marked trends. The friend said the report would be easier to explain to a product team than an API classification script.
Good to know
The product category is not named and the article shows no accuracy check on the scraped data. It was tested during the closed beta and the run was slow.
A prompt to try
Find <product type> listings on <platform 1>, <platform 2> and <platform 3>. Save product name, price and customer reviews to a CSV. Then group the negative reviews by cause, show how sentiment changed over the last <number> weeks, and list the three problems we should fix first, quoting example reviews.
Source
Runs on Alibaba QwenWork.
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