A casual dinner with friends turned into an unexpected revelation for Ms. Liu, a Beijing resident, when she discovered that three phones displayed three different prices for the same restaurant group-buying voucher. This wasn't an isolated incident. After days of investigation, it's becoming clear that "big data price discrimination" has evolved far beyond the old tactic of simply charging loyal customers more — it has morphed into a far more subtle "coupon game" that leaves consumers guessing.
Open the same link, and one person might be "hit" with a substantial discount coupon, while another scrolls endlessly without seeing a single cent of savings. The consumer's phone number, location, and even a casual repeat visit all influence the coupon amounts platforms distribute, which ultimately dictates the final checkout price.
Where the hidden inequality begins
Ms. Liu's frustration was palpable as she described the scene: "Three phones opened simultaneously, same voucher, yet the prices were all different." She and two friends were at a barbecue restaurant in Songjiazhuang, about to purchase a 500-yuan limited-time subsidized voucher from a platform. As all three opened the purchase page simultaneously, their screens displayed 470 yuan, 443 yuan, and 433 yuan respectively — a maximum difference of 37 yuan. The secret lay in an extra subsidy called "God Coupon," where the discounts varied wildly between accounts; one account received only a 5-yuan reduction, while another was slashed by 42 yuan.
Ms. Peng, a resident of Fangzhuang, stumbled upon a similar anomaly during a gathering with friends. At the same delivery restaurant, the same 22-yuan sweet and sour pork dish produced three different checkout prices: 9.68 yuan, 17 yuan, and 18 yuan — a near-doubling between the highest and lowest. Scrutinizing the details, the 9.68-yuan payment interface included a 12-yuan platform red packet and a 1.32-yuan premium subsidy card. "I didn't go out of my way to claim any red packets or premium cards — the system just issued them," Ms. Peng's friend explained.
Ride-hailing platforms show similar patterns. Ms. Zhao from Fengtai District noticed that on the same platform, with identical start and end points, higher-tier members were actually paying more. "As a high-tier member, I'm paying significantly more for my ride," she pointed out, showing her screen where the estimated fare for an economy ride was 22.8 yuan, with a "discount of 2.8 yuan" applied. Her husband, with a lower membership tier, received a 10-yuan discount on the same route, bringing his actual payment to just 15 yuan — a 7.8-yuan difference.
Mr. Wang from Chaoyang District also reported price discrepancies in online shopping. As a PLUS member, he purchased a lamb gift box for 238 yuan, while his wife, a non-member, paid only 228 yuan for the identical item. The reason: his wife received a system-issued "spend 200, save 20" coupon, while he was only given a "spend 100, save 10" coupon. Across these platforms, companies use an array of coupons to mask price differences, making differential pricing look like promotions rather than discrimination.
Why even premium members fall victim
Field testing reveals that the same product can display vastly different prices depending on who is looking, which device they use, and when they check. This "different price for the same item" phenomenon is especially pronounced in hotel bookings. Using an Android phone and an iPhone simultaneously, our search for the same hotel room near Qianmen in Beijing returned different results. The iPhone, logged into a "Black Gold Member" account, showed a 562-yuan deduction, bringing the final price to 550 yuan. The Android phone, a "Regular Member," received a 578-yuan deduction, resulting in a 534-yuan price. Convention suggests higher membership should mean bigger discounts, but the reality was exactly the opposite.
Adding a breakfast package to the same room type: the iPhone (Black Gold Member) saw a "new guest" discount of 408.31 yuan plus a "Black Gold 8.5折" discount, totaling 569.8 yuan. The Android (Regular Member) received a "new guest" reduction of 426.12 yuan plus a "limited-time upgrade" discount of 173 yuan, totaling 551.99 yuan — 17.81 yuan cheaper than the premium member. Notably, the "new guest" offer terms state clearly that "the discount amount is random, calculated dynamically based on account information and campaign activity." In other words, the platform uses an opaque, constantly shifting algorithm to determine who gets what.
The variability doesn't stop there. Refreshing the same room search on the same iPhone just 13 minutes later saw the price jump from 550 yuan to 658 yuan — an increase of over 100 yuan. The previously applied "new guest" and "Black Gold Member" discounts had vanished, replaced by a "Summer Special" offer, which carried its own disclaimer about "random discount amounts." When asked about this sudden price surge, platform customer service attributed it to "real-time changes in promotional activities," "temporary hotel adjustments," or "influences from agents," but admitted they couldn't pinpoint the exact cause. The response was vague: hotel prices are dynamic, and the specific reasons remain undisclosed.
A similar scenario unfolded on a food delivery platform. Ordering the same burger combo (originally 62.9 yuan) from two phones yielded different outcomes. The Android phone applied three discounts (an 18.1-yuan product discount, a 15-yuan flash-purchase red packet, and a 3.58-yuan premium card), bringing the total to 26.22 yuan. The iPhone, meanwhile, only received two of those discounts, with a smaller 9-yuan flash-purchase red packet, resulting in a final price of 35.8 yuan — nearly 10 yuan more. When questioned about why higher-tier members seem to get worse deals, the platform's customer service could only reply: "Discounts are random."
The regulation gap and the evolution of the practice
"Big data price discrimination has entered a new phase — it's more concealed, more contextual, and more refined," says Pan Tong, an assistant researcher at Peking University's Department of Sociology. "Platforms no longer set overtly different prices; instead, they bury the discrimination within personalized benefits like coupons, full-reduction promotions, and exclusive perks. The public price is the same, but the actual price paid varies — and ordinary consumers rarely notice."
Regulations have been on the books for years. The "Internet Information Service Algorithm Recommendation Management Provisions," effective March 2022, explicitly prohibit using algorithms to set unreasonable differential treatment in transaction conditions. The "Regulations on the Implementation of the Consumer Rights Protection Law," effective July 1, 2024, further stipulate that businesses cannot set different prices for the same product or service under equivalent transaction conditions without consumer awareness.
So does using randomly distributed coupons to influence final prices constitute a violation? "Using random coupon distribution to achieve differential pricing is also suspected of violating the fair trade and right-to-know provisions under the Consumer Rights Protection Law Implementation Regulations," asserts Chang Weidong, director of Beijing Changhong Law Firm. If platforms or merchants use algorithms to charge different prices to different consumers for the same product at the same cost, that constitutes "price discrimination."
Why does the practice persist despite the bans? "The 'black box' nature of algorithms makes them extremely difficult to penetrate, regulatory oversight struggles to keep up, and consumers often don't even realize they're being targeted," Pan Tong explains. Furthermore, algorithms adapt in real-time, capturing user behaviors like price comparisons, hesitation, and order cancellations to dynamically adjust pricing strategies — actively working to circumvent consumer attempts to compare, while making it hard for users to retain evidence.
Consumer counter-tactics and the path forward
"Big data price discrimination" has turned consumption into a game of information warfare. Faced with algorithms that size up every customer, younger consumers are developing their own counter-strategies. Xiao Lin, a recent graduate, has become quite adept at fighting back. She maintains accounts on Meituan, JD.com, Taobao, and Douyin, and meticulously compares prices before every order. She also registered three separate delivery accounts using her own phone number and her parents', and enabled privacy modes to limit app tracking. These "fresh accounts" — with almost no purchase history — often trigger the system's "retention" red packets, saving her around 15% compared to her long-standing accounts.
Our own testing confirmed this: on multiple platforms, "dormant accounts" with little activity frequently receive larger coupons, often exceeding 10 yuan. Social media is awash with tips for "fighting back against price discrimination" — clearing app caches, disabling precise location services, restricting app permissions, or even uninstalling and reinstalling apps after a few days as a "threat tactic."
But do these tricks actually work? Pan Tong cautions that platform algorithms possess powerful self-learning capabilities and will continuously track complete user behavior. A single "disguised low-price" tactic is easily identified and corrected. His recommendation is more systemic: platforms must take responsibility by proactively optimizing their algorithms, abandoning discriminatory pricing logic, and establishing fair, transparent pricing and discount mechanisms. He also advocates for platforms to publicly disclose their pricing rules and coupon distribution standards, allowing for social oversight and returning to the fundamental principle of technology serving the user.
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