Data Mining and Consumer Insights Since both consumers and businesses benefit from the use of data mining, each party must honor the right of the other in order to maintain a ethical function of data mining relationship between the two. Long ago, data mining was only about essential, voluntary information collected from customers who were aware that their information was being collected. Nowadays, the ethical questions raised concern whether the collected data will be used against the rights of customers and whether it will become an accessible part in the future by others. The strategies proposed by Payne and Trumbach, regarding data mining(1) and consumer information, propose that, in the right moral framework, data mining can be ethically effective and protective of consumer rights. Six principles are necessary for an ethical and productive data mining strategy: anonymity, disclosure, choice, time limits, trust, and data accuracy (Payne & Trumbach, 2009). First, let's discuss the issue of data mining and anonymity. This principle is based on the idea of ​​limiting personally identifiable data. He argues that to have ethical data mining, customers should be able to be anonymous whenever they have the chance. For example, a customer can purchase an order online only by using a username, password, and zip code (Danna & Gandy, 2002). Therefore, this customer will get the exact same service as anyone else without revealing their personal identity. This strategy is effective and useful as it protects the customer from unwanted exposure and, at the same time, meets their needs by offering them the same shopping experience as any other customer. On the other hand, some people might argue that in some situations, a... means of paper... they make the best choice in terms of personal data. The fourth issue involves data mining and the timeline that contains the duration of use of consumers' personal information. The next issue is about basic, secured, and extended trust. This strategy ethically protects the customer from any harm caused by disclosure as it requires not abusing consumer trust. It also helps the relationship between parties working together explicitly. The last issue discussed concerns the ethical principle of accuracy in data mining. Ethical data mining requires serving consumers as individuals and not depriving them of accurate service due to an inadequate aggregation system used by the company. To summarize, all the above six principles work ethically well together to meet consumers' needs, protect their privacy rights and provide them with the best customer services..