The Pros and Cons of Mining User Data to Provide Personalized Recommendations

The Pros and Cons of Mining User Data to Provide Personalized Recommendations

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Consumers today have high standards for determining what products meet their specific needs. As such, a satisfactory shopping experience is defined as one where consumers can quickly find what they’re looking for. Electronic commerce, or e-commerce for short, has addressed these high standards, allowing consumers to input search terms to narrow down an online retailer’s inventory to the item they’re looking for, and subsequently place orders from the comfort of their own home. However, online retailers must be quick in matching consumers with the products they want; if the customer feels that their search isn’t going well, they will simply leave the online retailer to complete a transaction with a competing retailer. This race to satisfy consumer needs gave rise to personalized recommendations, which are programmed suggestions for products that the online retailer believes consumers should consider buying. Consumers were startled as a result and became concerned with their privacy, questioning what information companies utilize to form these newfound recommendations. However, consumers should not be worried about their privacy; rather, they should continue engaging with these personalized recommendations in order to expand their search and bring themselves closer to a product of their interest, thus leading them to have a better online shopping experience.
The debate of privacy for generating personalized recommendations takes two standpoints: online consumers and companies. On the one hand, online consumers believe that companies invade their privacy by using sensitive information to generate these personalized product recommendations. On the other hand, companies argue that their personalized product recommenda...


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