Walmart, the country's biggest retailer, removed a prepaid mobile internet stick from its website earlier this year after noticing a number of unhappy comments uploaded by customers.
Upon looking into the problem, it learned that the wireless carrier had not activated these sticks, a task which was conducted remotely. The product was returned to Walmart.com within two days.
"We're using that real-time feedback to help suppliers improve products faster," Greg Hall, Walmart.com's vice president of marketing, told the Wall Street Journal.
Similarly, LL Bean, the apparel, homewares and outdoor chain, discovered that Supima Cotton Fitted Sheets, among its top-selling items, were receiving extremely critical online user reviews.
The organisation suspended this line from its ecommerce site, and further investigation showed a wrinkle-resistance treatment, added in error by a contractor, had resulted in the fabric unravelling.
Having become aware of this issue, LL Bean then offered new sheets to the 6,300 people who had bought the faulty ones.
"Before, it would have taken us months and months to figure out if something was wrong with the product through returns, if we ever would have known at all," Steve Fuller, LL Bean's chief marketing officer, told the Wall Street Journal.
Now, LL Bean regularly delists items from its website where they are consistently given less than three star ratings, although the problem of how to deal with these goods when they are improved has been difficult.
As an example, neither putting the product back onto the web alongside pre-existing negative reviews or selling it under a different name seem to solve the problem. "It's a challenge we haven't quite figured out yet," said Fuller.
Based on rigorous data mining, Amazon, the ecommerce pioneer, has integrated recommendations into almost all aspects of its system, from its "Frequently bought together" to "Customers who viewed this also viewed" features.
Sucharita Mulpuru, an analyst at Forrester, the research firm, suggested the conversion to sales of Amazon's on-site recommendations can reach 60% in some cases.
Despite this, she argued greater sophistication could still be achieved, stating: "There's a collective belief within the e-commerce industry that Amazon's recommendation engine is a suboptimal solution."
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