Alibaba QwenWork · Alibaba Cloud
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 half a day or more came out in one run.
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 run took about 30 minutes. The friend said it separated positive and negative reviews, grouped the problems and marked trends, and would be easier to explain to a product team than an API classification script.
Worth knowing
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.
Try it with Alibaba QwenWork
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.
Swap the parts in angle brackets for your own details. This prompt is adapted from the case, not copied from the original.
What this label means: User story
Someone using it at work posted about it. Any numbers are theirs, so we write "the poster says".
Summarised from the original source; the link has the full story. The people and companies here are not Wize customers.