AI-driven big data pricing penalizes loyal customers in China
Consumer associations in Beijing, Tianjin and Hebei conducted a survey on big data differential pricing and found that over 40% of consumers reported experiencing price discrimination, with loyal customers charged higher prices for shopping, food delivery and ride-hailing services. The associations called for stricter regulations and improved corporate governance to protect consumer rights.
What happened
Consumer associations in Beijing, Tianjin and Hebei jointly conducted a survey combining questionnaires and experiential testing across eight internet consumption platforms: online shopping, tourism, accommodation, food delivery, ride-hailing, ticketing, short-video/livestreaming, and bike-sharing.
Results showed that over 40% of respondents reported encountering differential pricing based on big data, with price increases following multiple product views, different discounts for different users, hidden coupons for existing customers, and varying prices for the same product at the same time.
Reported impact
Over 65% of respondents expressed concern about privacy breaches and differential marketing practices. Long-term customers reported being charged higher prices without clear justification, which respondents considered unfair treatment.
The experiential survey found that new users often receive lower prices through exclusive coupons, while user level, membership status and payment methods also affect final pricing.
Index analysis
Respondents found it difficult to distinguish between standard differential marketing and big data-driven differential pricing, typically defining the latter as long-term customers being charged more without apparent reason.
About one-third of respondents believed big data benefits outweigh harms, one-fifth held the opposite view, and over one-third believed both sides balance out. The survey identified shopping, food delivery and ride-hailing as the areas where differential marketing occurs most frequently.
Governance controls
The three consumer associations recommended stronger regulations for industry development, requiring enterprises to strengthen internal management, ensure honest operations, and establish sound data usage protocols. They called for stricter laws defining big data differential pricing standards and increased penalties for violations.
Recommendations also included encouraging technological innovation, promoting information transparency, creating fair competition environments, and educating consumers to increase vigilance and self-protection when encountering violations.
Classification
Sources and evidence
Sources not yet published
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