年中大促的营销周期里，“节前调价、节中让利”的操作早已脱离偶发营销行为范畴，成为国内电商平台节点性促销期间的普遍惯例。本次观测样本显示，部分日常售价稳定在499元的家居日用品类商品，会在大促活动启动前15天左右将页面标示的“日常基准价”抬升至899元，大促上线后立即标注“直降400元”，最终结算价回落至原有499元的日常水平。该模式下消费者感知到“直降400元、到手价仅为原价5.5折”的让利信号，但实际并未获得任何真实价格优惠，属于典型的营销信号偏差行为。
这种消费者明知套路普遍存在、却仍难以规避决策偏差的现象，并非个体理性不足导致，其底层驱动来自两个已经经过行为经济学领域大样本实证检验的经典决策机制：
1. 锚定效应（Anchoring Effect）：虚假价格锚点的感知劫持
诺贝尔经济学奖得主丹尼尔·卡尼曼在其经典实验中验证了锚定效应的作用路径：受试群体先转动产出随机数值的轮盘，再对“非洲国家在联合国成员国中的占比”这一客观事实进行估值，最终轮盘转出高数值的受试群体，给出的估值结果系统性显著高于轮盘转出低数值的群体。该实验证实：个体进行不确定性判断时，会产生“锚定依赖”——即决策过程会过度锚定最先接触到的初始信息，即便该信息完全随机、与决策目标无关甚至完全虚假，个体也不会主动启动认知资源对锚点的真实性进行核验，仅会以锚点为基准做后续的有限调整。
落地到电商促销场景中，消费者进入商品详情页后，视觉优先级最高的“建议原价899元”就是商家刻意投放的虚假高锚点：当不存在该锚点时，单独告知消费者商品日常售价499元，消费者会基于同类竞品价格带建立独立的价值判断；而899元的锚点介入后，消费者的比价参照系会被直接替换为该虚高数值，最终产生“直降400元性价比极高”的错误感知，锚定效应的决策助推作用完全生效。
2. 损失厌恶（Loss Aversion）：限时场景下的本能决策唤醒
行为经济学的前景理论（Prospect Theory）明确界定了损失与收益的效用权重差异：同等量级的损失带来的负向效用强度，是收益带来的正向效用强度的2~2.5倍。这种认知偏好是人类在长期演化过程中形成的硬编码决策机制：原始社会场景下，失去存量食物的后果是直接面临死亡风险，而额外获得增量食物仅能提升短期生存舒适度，由此人类大脑演化出了对损失信号的高敏感性，将规避损失置于比获取收益更高的决策优先级。
在“先抬价后折价”的场景中，虚高锚点已经让消费者预先形成了“可省400元”的收益感知，叠加大促标配的“限时24小时”“库存剩余3件”“专属优惠券过期即作废”等稀缺性提示，消费者会本能将“错过折扣恢复899元原价”感知为确定性损失，决策行为完全由本能的损失规避动机驱动，而非基于自身真实需求与商品日常价值的理性核算。两类效应形成叠加助推后，用户完成下单几乎是自动化的条件反射行为。
从合规维度看，绝大多数“先抬价后折价”的操作已经落入《价格法》界定的价格欺诈范畴，历年各级市场监管部门在618、双11等节点前都会公开通报多起此类违规处罚案例。但该行为的合规判定长期面临现实阻碍：商家普遍采用新建商品链接、微调商品规格/型号/上架主体身份的方式，在抬价区间内完成数笔低额度自交易，将原本完全虚构的虚高原价包装成有真实交易记录的“历史成交价”，以此抗辩价格欺诈的指控，大幅提升了行政违法认定的取证与判定成本。
而作为交易规则制定方的电商平台，尽管当前普遍上线了历史价格展示、价保服务等消费者保障工具，但一方面多数平台比价模块的溯源周期仅覆盖7-15天，远短于用户需要的全周期价格参照维度，同时商家可以通过下架旧链接、替换商品ID的方式直接让价格对比、价保机制完全失效；更深层的动因是平台的核心业绩考核指标GMV（商品交易总额）直接决定其资本市场估值与行业话语权，平台本身不存在全面清退此类高转化营销模式的原生动力，仅在接到消费者正式投诉后，对涉事商家采取扣分、降权、限制活动报名等低惩戒成本的处置措施，约束效力极其有限。
放在宏观经济语境下，该现象是多方目标动态博弈下的系统自然后果：宏观层面需要通过大促节点拉动居民消费、扩大内需，商家面临激烈的存量市场竞争需要以高感知让利的方式撬动更高成交规模、保障经营利润，消费者则始终追求“性价比最大化”的消费体验，三者的诉求交织下，“先抬价后折价”形成了当前均衡状态下的灰色生存空间——它既不符合合规营销的理想范式，但其普遍存在本身，就是多方目标未完全对齐时市场演化出的客观现实。
During mid‑year shopping‑festival marketing cycles, the practice of “raising prices before sales and offering apparent discounts during campaigns” has evolved from occasional marketing tactics into a pervasive norm for major promotional events across Chinese e‑commerce platforms. Observed samples show certain home‑and‑daily‑use goods with a stable regular price of ¥499 will have their displayed “baseline regular price” inflated to ¥899 roughly 15 days prior to campaign launch. Once the promotion goes live, merchants immediately mark a “¥400 direct cut”, bringing the final checkout price back to the original ¥499 regular level. Under this scheme, consumers perceive a genuine bargain: “¥400 off, final price at merely 55 % of original price”, yet receive no real price reduction at all. This represents a typical case of misleading marketing signalling.
This phenomenon — consumers being broadly aware of such tricks yet still susceptible to biased decision‑making — stems not from individual rationality deficits. Its underlying drivers are two well‑documented classical decision‑making mechanisms empirically validated by large‑scale behavioural‑economics research:
1. Anchoring Effect: Perceptual Hijacking via Fictitious Price Anchors
Nobel laureate Daniel Kahneman demonstrated how the anchoring effect operates in his landmark experiment. Participants first spun a wheel generating random numbers, then estimated the share of African nations among UN member states. Subjects who drew high wheel values consistently produced significantly higher estimates than those who drew low values. The experiment confirms anchoring dependence in human judgement: when making judgements under uncertainty, people over‑rely on initial information they encounter. Even where such information is entirely random, irrelevant or outright false, individuals rarely expend cognitive effort verifying anchor authenticity, and only make limited adjustments based on that starting reference point.
Translated to e‑commerce promotion scenarios: upon opening a product detail page, the visually prominent “suggested original price ¥899” functions as a deliberately planted false high anchor. Without this anchor, consumers presented with a regular price of ¥499 would form independent value judgements against comparable competing products. Once the ¥899 anchor is introduced, consumers’ reference frame for price comparison is supplanted by this inflated figure, yielding the misleading perception that “¥400 off delivers exceptional value”. The anchoring effect exerts its full biasing influence.
2. Loss Aversion: Instinct‑Driven Decision‑Making Under Time‑Limited Conditions
Prospect Theory in behavioural economics formalises the asymmetric utility weight between losses and gains: negative utility triggered by a loss is 2‑2.5 times stronger in magnitude than positive utility from an equivalent‑sized gain. This cognitive predisposition constitutes an evolution‑hardwired decision mechanism. In prehistoric settings, forfeiting existing food stocks carried immediate mortality risks, whereas obtaining extra food only improved short‑term comfort. The human brain accordingly evolved heightened sensitivity to loss signals, prioritising loss avoidance over gain acquisition.
In “pre‑sale price‑inflation” scenarios, the fictitious high anchor already creates an anticipatory sense of gain: “I can save ¥400”. Coupled with standard promotional cues — “24‑hour‑only”, “only 3 units left in stock”, “exclusive coupon expires soon” and other scarcity prompts — consumers instinctively interpret “missing the discount and reverting to ¥899” as a definite loss. Purchasing decisions become driven primarily by instinctive loss‑avoidance impulses rather than rational assessment of personal needs and inherent product value. When both effects reinforce each other, completing a purchase becomes nearly automatic, reflex‑like behaviour.
From a compliance perspective, most “raise‑then‑discount” practices fall under price fraud as defined by China’s Price Law. Market‑regulation authorities at all levels regularly publish penalty notices for such violations ahead of major shopping events including 618 and Double 11. Nonetheless, factual obstacles persist in enforcement adjudication. Merchants frequently create new product listings, tweak item specifications or alter selling‑entity identities. Within the pre‑promotion price‑hike window, they generate small‑volume self‑transactions, fabricating “historical transaction records” to justify inflated baseline prices and refute price‑fraud allegations. This substantially raises evidentiary burdens and complicates administrative violation rulings.
E‑commerce platforms, as rule‑setters, have rolled out consumer‑protection tools such as historical‑price displays and price‑guarantee services. Yet price‑comparison modules typically only trace pricing for 7‑15 days, far shorter than the full‑cycle reference consumers require. Merchants can render price‑comparison and price‑guarantee features completely ineffective simply by removing old listings and changing product IDs. More fundamentally, core performance metric GMV (Gross Merchandise Volume) directly shapes platforms’ capital‑market valuations and industry leverage. Platforms lack intrinsic incentives to fully eliminate these high‑conversion marketing patterns. Sanctions are mostly low‑cost remedies imposed only after formal consumer complaints: point deductions, search‑ranking demotion and restricted campaign eligibility, carrying limited deterrent power.
Within the broader macroeconomic context, this phenomenon emerges endogenously from dynamic multi‑stakeholder trade‑offs. Macroeconomic policy seeks to boost household consumption and domestic demand via shopping festivals. Merchants face fierce competition within saturated markets and rely on perceptually attractive discount messaging to drive transaction volumes and safeguard margins. Consumers pursue maximum perceived value for money. Intertwined priorities create a grey‑zone equilibrium for “raise‑then‑discount” tactics. While inconsistent with ideal compliant‑marketing standards, its widespread prevalence represents an objective market outcome where stakeholder objectives remain misaligned.