They can even use "big data to kill" both consumers and service providers to benefit themselves. Therefore, this method is a strong attraction for merchants. It can be seen from the above cases that the essence of "big data killing" is actually that merchants collect data to find the "highest price that users can afford" for each product, so as to maximize profits. But profit comes with risk, and although this approach maximizes the platform’s profits, consumers won’t easily pay for it. In the "2018 Survey Report on Chinese Netizens'
Attitudes and Behaviors of "Big Data Killing Familiarity" released by iiMedia Research, 77.8% of the interviewed netizens would think that it is unacceptable for service applications to use big data for differential pricing, and those who think it is b2b data acceptable. Internet users only accounted for 12.2%. A more serious consequence is that the report shows that 42.9% of the interviewed netizens said that they would consider changing applications because the applications use big data for differential pricing; 40.5% of the interviewed netizens would think that if the applications they use use big data for differential pricing, they will be priced differently in the future.
Will not use the app again. Take Amazon as an example. After it was discovered that it had launched differential pricing, as the news spread, more and more old users who had been "pitted" knew about it. In a denunciation, many people publicly stated that they would never do it again. Will not buy anything on Amazon. In the end, the matter got bigger and bigger, until Amazon CEO Bezos personally apologized and refunded the price difference of the goods before it gradually calmed down.