Precision-information pushing stems from the combination of traditional internet information provision services and big-data analysis. With the emergence of big-data-analysis methods, providers of information services have gradually brought in the information service model of precision-big-data pushing, e.g., portals, certain search engines and some providers of content services, which make available article pushing through mobile apps. However, while bringing user loyalty, precision-information pushing may also give rise to the problem of “discrimination”, where technical means help deprive the user of his or her right to obtain information at his or her own discretion or in a fair manner.
With e-commerce laws taking effect, new rules on the precision pushing of online information have been put in place, lifting precision-information pushing to the heights of users’ right to choose and non-discrimination, thereby placing new requirements on internet operators.
Meaning of and application scenarios for precision pushing of online information. Precision-information pushing is one of the typical scenarios of big data application. The term “precision pushing” means the process of constructing a mass user profile, based on big data analysis and, through linking the identification tags in user profiles with identity information of internet users, accurately finding the user and pushing various types of information to him or her.
There may be two to three aspects of precision-information-pushing scenarios:
- Completing the pushing of specific knowledge and information, based on individual preferences. For example, analyzing the browsing preferences of a specific user, based on his or her searches and browsing history on search engines and portals and, then, the next time the user opens his or her browser, directly displaying for him or her information relating to his or her preferences, thereby achieving personalized recommendation results in search or online page views.
- Displaying different goods, based on a user’s preferences. This scenario is like information pushing, as the online operator discovers the user’s potential product preferences, based on his or her browsing or purchase history and then displaying its different products on different pages.
- Price-discrimination problem. Price discrimination realized through precision-information pushing, i.e., the so-called “big-data swindle”, refers to an online operator providing identical goods or services to different consumers at varying sales prices. Price discrimination is an economics term and is usually neutral. However, displaying different prices to consumers with varying purchasing power through a big-data analysis runs counter to the rule of clear marking of prices in the Law on Protection of the Rights and Interests of Consumers. Additionally, this denies users the right to obtain price listings in a fair manner.
“Non-discrimination” rule. E-commerce law legally defines and regulates the issue of “non-discrimination” in precision-information pushing for the first time, with Article 18 of the said law specifying that, “where an e-commerce operator provides search results on merchandise or services, based on such traits of a consumer as his or her interests, consumption habits, etc, he or it shall additionally provide him or her choices that are not a reflection of his or her personal traits, and respect and protect consumers’ lawful rights and interests in a non-discriminatory manner”. This rule contains three layers of meaning, which can be interpreted as follows:
- It legally defines precision-information pushing (precision marketing) for the first time. The expression for precision-information pushing used in the aforementioned provision is, “where an e-commerce operator provides search results on merchandise or services, based on such traits of a consumer as his or her interests, consumption habits, etc.” From this provision, it can be seen that the core of precision-information pushing is construction of a model for analyzing consumers’ interests and consumption habits, which is also what we have termed a “user profile”.
- It sets forth restrictions on precision marketing. On the basis of its definition of precision-information pushing, the aforementioned provision also places restrictions on precision-information pushing, namely “it shall additionally provide him or her choices that are not a reflection of his or her personal traits”. What are “choices that are not a reflection of his or her personal traits”? A literal understanding of the meaning is that the consumer should be given the right to choose. That is to say, when a consumer opens a page on an e-commerce platform or an information platform, the enterprise is required to provide two types of platform pages. One is a display page “customized”, based on his or her consumption habits and interests, and the other being a conventional page that has not undergone big-data analysis.
- Respecting and giving equal protection to consumers’ lawful rights and interests. In fact, the provisions of Article 18 are those set forth over consumer-protection issues that precision-information pushing could trigger, restricting internet operators from denying consumers the right to choose.
Response of Internet operators. For internet operators, Article 18 of the e-commerce laws signifies legal restrictions on precision-information pushing (or precision marketing). For e-commerce operators that provide precision information pushing, the following two response strategies are available:
- Expressly stating that the page has precision-information-pushing functions, i.e., expressly informing the user that the information displayed on the page is provided after big-data analysis and is directionally pushed based on the characteristics of his or her acts and consumption preferences. Additionally, this notification should be displayed in a prominent location on the web page to facilitate recognition.
- Providing the conditions that allow users to exercise choice. After notification, the web page should have an appropriate clickable button or another easy method to allow the user to exercise his or her right to choose.
Wu Weiming is a senior partner at AllBright Law Offices
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