The Vicious Marketing Cases in the Digital Marketing Era

Recently, a terrible marketing case has exposed in China – the “Shashu” incident of Didi Dache software. Users with different levels of spending locate the starting and destination at the same address, but the budget price appears different at the same distance. The final result also directly leads to different fees paid by customers at the same distance.

As we can see above, the same starting and destination, the same distance, the same service chosen (Express Service), but according to the different “individual” users, there have been different costs. Here “individual” refers to the background data according to the collected user data, analyzing the user’s economic consumption level. That is, whether the user is a new user or a regular user, the gender and age of the user (usually older persons over 50 years old see the price beyond his acceptable range, then he will choose another cheaper way to going out) and so on. According to the characteristics of these individuals, big data customizes the price of a specific user.

After this incident broke out, other consumers also found discriminatory treatment of users in some popular apps in China. For example, if you book a hotel room, if you have booked a room before you have to increase the price, then the price of the room displayed in your app is higher than that of other users. And the prices that are often seen by regular customers using the same app booking room are higher than those of other ordinary users.

For these phenomena, Chinese media have given a new name, “big date Shashu”. That is, “price discrimination” in the market and economic fields. The word “Shashu” is intended to refer to a social phenomenon in China. It speaks of relatively familiarity between people and people. In China’s inherent social relations, some people think that if they find someone who you are familiar with or you have a good relationship with them, then this person will certainly make some sacrifices for you giving up some of their own interests. So when you need help, you will take it for granted that based on your good relationship, this person will not do something bad for you. However, in fact, he sought a higher level of personal interest from the process.

With the development of the market economy and the erosion of the relationship between acquaintances and the economic rationality, in the society , there are some behaviors that are specifically aimed at gaining acquaintances to seek benefits, which is “Shashu”. This phenomenon is no longer a new phenomenon in previous marketing, but in the era of digital marketing, this is a new expression of an old problem. Combined with big data, the so-called “Big date Shashu” is an online business that uses its own user data and analyzes it to make price discrimination against regular users. That is to say, the same product or the same service, the price displayed by the online merchant to the regular user is higher than the price seen by the new user, and the profits are maximised in turn (compared with the normal marketing strategy).

The price discrimination in the era of big data can be traced back to Amazon’s “Experiment” of Product-different Pricing in 2000. In that year, users found that the price of “Titus” discs for regular customers was $26.24, but after the cookie was deleted, it was found that the quotation had become $22.74. The exposure of this matter has caused Amazon to face condemnation from consumers. The CEO Bezos personally apologized, saying that everything was just for “experimental.” Whether or not this is just an “experiment” is unknown, but adjusting prices to “chasing profits” is unquestionable.

In price discrimination, profit maximization is Personalized pricing (or first-degree price differentiation) — selling to each customer at a different price; this is also called one-to-one marketing. The optimal incarnation of this is called perfect price discrimination and maximizes the price that each customer is willing to pay.

In the traditional market, it is difficult to find the phenomenon of Personalized pricing in real life. However, with the advent of the era of big data, and with consumers not knowing, the background data, as well as the attributes of individual personal belongings of electronic products, almost provides all feasible conditions for the phenomenon of Personalized pricing. It can charge the maximum amount of money that can be paid by each individual consumer. The emergence of most software apps now meets the conditions for implementing Personalized pricing.

In addition to the above behaviors, big data can also be based on the geographical location of the Product-different Pricing strategy. If you are near a shopping mall, give a price increase for the goods you see. There are few shopping malls around you, so it is inconvenient for you to compare prices, and the possibility of business failure is low, so you have to buy for raising prices. Many years ago, the United States had a case of “showing higher pizza prices to users if there were no KFC nearby.” Or use keywords, time, and frequency that you and your friends use search engines to determine whether you are “look at it casually” or “intention to buy” or even “strongly desire to buy” (for example, if a family member gets sick or something like that), thereby giving you (and your entire social relationship circle) adjustments to the offer…

At present, many platforms have denied that they use big data “Shashu”, but complaints and reports of such incidents are always taking place. What users generally care about is whether this is a common phenomenon in the industry, or whether individual businesses use the user’s personal privacy data.

Usually we all think that big data adds a lot of positive convenience to our lives, but most users are never aware of it when they are blinded by the convenience of the moment, including that although I was very careful to protect personal privacy, When it came to this news, I was still shocked. Does this behavior really maximize profits?

From the above, we can see at least two very serious problems in bad digital marketing based on big data. Legally we are infringed not only on personal privacy rights but also on our rights as consumers. The business ethical issues of commercial businesses have also been criticized by the general public in marketing. Technology companies arbitrarily slaughter consumers through technological and network monopoly status. The same platform has different prices for different consumers. This kind of big data “Shashu” has been an illegal act. It violates the reasonable rights of consumers and may also be suspected of price fraud.

After seeing this news, I will think about my own experience. I really like the collection of cups. After I saw some Japanese masters’ handmade artworks on Taobao, I clicked on the collections, but after some time I discovered that the prices I could receive from my collection changed, from what I could accept at the very beginning to what I could not accept. When I clicked on the collection, I was thinking that I would afford it if I make money later, so I clicked on the collection. However, the background data automatically analyzes that I am a user who can afford this price, so according to my collection, Taobao will continue to recommend me a higher-priced cup. Until I can not afford one of the cups. Finally, I looked at my collection of records, the price is very amazing. Because I finally collected a lot of hundreds of dollars worth of cups. What followed was that when I opened the Taobao page again, the other products on the page were also products that were higher than the prices that had been displayed.

I think the exposure of this bad marketing event is not a bad thing. On the contrary, it offers us a wake-up call when we choose to ignore its negative side because of the positive aspects of big data. In the era of digital marketing, the balance between the follow-up of laws and institutions, the shaping of business ethics, and the formation of business order need to be more complete and faster than the institutional rules in the traditional market economy.

Reference

http://wiki.mbalib.com/wiki/%E5%A4%A7%E6%95%B0%E6%8D%AE%E6%9D%80%E7%86%9F

http://china.cnr.cn/yaowen/20180325/t20180325_524175733.shtml

http://mobile.zol.com.cn/683/6835206.html