Views while purchasing on Amazon or similar platforms
When making purchases on Amazon or similar platforms, I habitually rely on user ratings as a crucial factor in my decision-making process. Specifically, I prioritize negative reviews to gauge potential issues or shortcomings with the product. By understanding the criticisms, I can weigh them against the positive feedback to make a more informed decision. Additionally, I find value in browsing through photo comments provided by users, as visual evidence can offer further insight into the product’s quality and appearance, enhancing my confidence in the purchase. Considering the principles of social computing, it’s evident that a myriad of data is collected about customers during online transactions. In the case of a recent purchase, various types of information were likely gathered about me, including:
1. Product views: The platform would have recorded which products I browsed, indicating my interests and preferences.
2. Frequency of views: The number of times I viewed a particular product could suggest the level of interest or consideration I had for it.
3. Related product views: Data may have been collected on other items I explored in conjunction with the initial product, revealing potential cross-selling opportunities or complementary items.
4. Interaction with reviews: My engagement with user reviews, such as which reviews I read and whether I found them helpful, could provide insights into my decision-making process.
Businesses can leverage this information in several ways:
1. Personalized recommendations: By analyzing my browsing history and purchase behavior, the platform can offer tailored product recommendations suited to my preferences, increasing the likelihood of future purchases (Resnick & Varian, 1997).
2. Targeted marketing: The data collected can inform targeted advertising campaigns, ensuring that promotional materials are relevant to my interests and shopping habits (Hann et al., 2002).
3. Product improvement: Feedback gathered from user reviews, including my own, can be used by businesses to identify areas for product enhancement or refinement, ultimately improving customer satisfaction (Dellarocas et al., 2007).
Customer data is indeed a valuable commodity that can be sold or exchanged between businesses, advertisers, and third-party data brokers (Acquisti & Grossklags, 2005). However, this practice raises concerns regarding privacy and data security. Customers may be uncomfortable with the idea of their personal information being shared or monetized without their consent, especially if it leads to unwanted solicitations or invasions of privacy. Additionally, there are ethical considerations regarding the responsible use of customer data, ensuring that it is handled in a transparent and ethical manner to maintain trust and integrity in the business-consumer relationship (Milne & Gordon, 1993).
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