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打击虚假交易!淘宝天猫优化商家评分逻辑

亿邦动力 2026-01-22 10:43
亿邦动力 2026/01/22 10:43

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淘宝天猫发布新规则以打击虚假交易,优化商家评分逻辑,旨在维护真实评分环境。

1. 订单不累计销量和评论的情形:支付价格显著偏离正常售价区间(例如低于一口价3折且低于1元)、修改或删除SKU导致商品核心信息变更、平台通过大数据技术认定为异常的订单,这些情况将屏蔽评论并删除销量。

2. 低于1元支付订单的处理:销量正常累计;买家绑定有效手机时评价累计,否则卖家端评价最多250笔,买家端不受影响。

3. 商品类目调整规则:转入或转出特定一级类目(如个性定制类、手机类等),近30天销量全部删除;其他一级类目调整,1元以下支付订单销量删除;定制类目与其他类目互调,销量全部删除不累计。

新规则影响品牌定价和消费者信任管理,提升真实营销环境。

1. 品牌定价策略:规则禁止价格异常偏离(如支付价低于一口价3折且低于1元),否则销量不计,促使品牌商合理设置折扣避免误导性定价竞争。

2. 消费趋势与用户行为:打击虚假交易可提升平台真实度和用户信任,间接加强品牌形象;用户行为方面,买家账号绑定手机影响评价累计,需关注用户验证机制以优化互动。

3. 产品研发启示:避免通过SKU修改变更商品核心信息,确保产品更新合规,以维护评分真实性和消费者忠诚度。

政策解读新规则变化,带来风险与机遇,助力健康经营。

1. 政策详细解读:订单销量和评论不累计情形包括价格异常(低于一口价3折且低于1元)、SKU变更致商品实质改变、异常订单,卖家需调整定价策略规避风险。

2. 风险提示:类目调整不当(如转入特定一级类目)导致销量清零;支付低于1元订单若买家未绑定手机,卖家评价受限250笔,需注意运营合规。

3. 机会与应对措施:平台推出AI假图识别模型和争议处理规则,帮助反内卷;规则降低虚假竞争,创造公平环境,卖家可学习优化服务获取增长;合作方式包括绑定用户手机以提升评价权重。

规则启示产品设计和电商数字化推进,创造商业机会。

1. 产品生产需求:避免SKU修改导致商品核心变更,确保设计一致性以维持销量累计;类目调整规则(如特定定制类目)需谨慎管理产品分类。

2. 商业机会:平台优化环境减少虚假交易,真实产品易获增长;推进电商数字化时,遵循定价规则(如价格不低于1元异常设定)可提升评分可信度。

3. 电商启示:类目管理规则(如从定制类目转出销量清零)提示需标准化产品上线流程,减少调整避免损失,拥抱健康生态。

行业趋势与新技术应用解决客户痛点,提供优化方案。

1. 行业发展趋势:平台持续优化经营环境(如打击虚假交易),提升风控机制成为电商主流趋势。

2. 新技术:引入大数据技术检测异常订单和AI假图识别模型,解决售后纠纷痛点,助力服务效率提升。

3. 解决方案:针对虚假交易痛点,规则提供订单屏蔽机制(价格异常、SKU变更、异常识别),服务商可借鉴开发类似工具;平台互信机制和账号诚信体系可作为行业参考模板。

平台做法解决商业需求,优化招商和风控管理。

1. 最新规则:明确屏蔽虚假订单销量和评论(价格异常、SKU变更、异常订单),解决公平竞争需求;类目调整规则管理流量,避免销量虚高。

2. 运营管理:实施账号诚信体系与互信机制,强化商家关系;支付低于1元订单处理细节(评价限制)需精细运营。

3. 招商与风规避:健康环境吸引商家(如反内卷举措),通过AI工具和争议规则降低风险;特定类目名单(如定制类)帮助定向招商和规避虚假风向。

产业动向与政策启示揭示商业模式创新和规范。

1. 产业新动向:淘宝天猫优化评分规则打击虚假交易,代表电商平台治理强化趋势;引入大数据和AI技术,标志产业技术升级。

2. 新问题与政策启示:虚假交易定义(价格偏离、SKU变更)提供法规建议框架,可应用于电商规范;类目调整规则启示政策制定需细化分类管理。

3. 商业模式:平台互信机制和账号诚信体系创新商家关系;健康环境促进确定性增长,可作为其他行业借鉴模型。

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声明:快读内容全程由AI生成,请注意甄别信息。如您发现问题,请发送邮件至 run@ebrun.com 。

我是 品牌商 卖家 工厂 服务商 平台商 研究者 帮我再读一遍。

Quick Summary

Taobao and Tmall have introduced new rules to combat fake transactions and optimize merchant rating logic, aiming to maintain an authentic review environment.

1. Orders that will not accumulate sales volume or reviews include: those with a payment price significantly deviating from the normal price range (e.g., below 30% of the fixed price and under 1 RMB), those where SKU modifications or deletions change core product information, and those identified as abnormal by the platform's big data technology. Such orders will have reviews blocked and sales deleted.

2. Orders under 1 RMB: Sales volume will be counted normally. Reviews will accumulate if the buyer has a bound valid mobile number; otherwise, a maximum of 250 reviews will count on the seller’s side, with no impact on the buyer’s side.

3. Product category adjustment rules: When switching into or out of specific first-level categories (e.g., personalized customization, mobile phones), all sales from the past 30 days will be deleted. For other first-level category adjustments, sales from orders under 1 RMB will be deleted. Switching between customization categories and other categories will result in all sales being deleted and not counted.

The new rules impact brand pricing and consumer trust management, enhancing the authenticity of the marketing environment.

1. Brand pricing strategy: The rules prohibit significant price deviations (e.g., payment price below 30% of the fixed price and under 1 RMB), otherwise sales won't count. This encourages brands to set reasonable discounts and avoid misleading pricing competition.

2. Consumer trends and user behavior: Cracking down on fake transactions improves platform authenticity and user trust, indirectly strengthening brand image. Regarding user behavior, review accumulation depends on buyers having a bound mobile number, highlighting the need to focus on user verification mechanisms to optimize interaction.

3. Product development insights: Avoid changing core product information through SKU modifications to ensure compliance during product updates, thereby maintaining rating authenticity and consumer loyalty.

The new policy changes present both risks and opportunities, aiding healthy business operations.

1. Policy details: Situations where order sales and reviews won't be counted include abnormal pricing (below 30% of the fixed price and under 1 RMB), SKU changes that alter the product's essence, and abnormal orders. Sellers must adjust pricing strategies to mitigate risks.

2. Risk warnings: Improper category adjustments (e.g., switching into specific first-level categories) can lead to sales being reset. For orders under 1 RMB, if the buyer lacks a bound mobile number, seller reviews are capped at 250; operational compliance is crucial.

3. Opportunities and countermeasures: The platform's AI fake image detection model and dispute resolution rules help combat internal competition. The rules reduce fake competition, creating a fairer environment. Sellers can learn to optimize services for growth, such as encouraging buyers to bind mobile numbers to increase review weighting.

The rules highlight implications for product design and e-commerce digitalization, creating business opportunities.

1. Product production needs: Avoid SKU modifications that change core product information to maintain sales accumulation. Carefully manage product classifications, especially regarding category adjustment rules (e.g., specific customization categories).

2. Business opportunities: A platform environment optimized to reduce fake transactions makes it easier for genuine products to grow. Adhering to pricing rules (e.g., avoiding abnormal prices below 1 RMB) enhances rating credibility during e-commerce digitalization.

3. E-commerce insights: Category management rules (e.g., sales reset when switching out of customization categories) emphasize the need to standardize product listing processes, minimize adjustments to avoid losses, and embrace a healthy ecosystem.

Industry trends and new technology applications address client pain points, offering optimization solutions.

1. Industry development trends: Platforms continuously optimize the business environment (e.g., combating fake transactions), making enhanced risk control a mainstream e-commerce trend.

2. New technologies: The introduction of big data for detecting abnormal orders and AI fake image recognition models addresses post-sale dispute pain points, improving service efficiency.

3. Solutions: To tackle fake transactions, the rules provide order shielding mechanisms (for price anomalies, SKU changes, abnormal detection). Service providers can develop similar tools based on this. The platform's mutual trust mechanism and account credibility system can serve as industry reference models.

Platform practices address commercial needs, optimizing merchant recruitment and risk control management.

1. Latest rules: Clearly block sales and reviews from fake orders (due to price anomalies, SKU changes, abnormal orders), addressing the need for fair competition. Category adjustment rules manage traffic flow and prevent inflated sales figures.

2. Operational management: Implement an account credibility system and mutual trust mechanism to strengthen merchant relationships. Fine-tuned operations are needed for handling orders under 1 RMB (review restrictions).

3. Merchant recruitment and risk avoidance: A healthy environment attracts merchants (e.g., anti-internal competition measures). AI tools and dispute rules mitigate risks. Specific category lists (e.g., customization) aid targeted recruitment and avoid fake trends.

Industry movements and policy implications reveal business model innovation and standardization.

1. Industry trends: Taobao and Tmall's optimized rating rules to combat fake transactions reflect a broader trend of strengthened e-commerce platform governance. The adoption of big data and AI signifies industry-wide technological upgrades.

2. New issues and policy implications: The definition of fake transactions (price deviation, SKU changes) provides a framework for regulatory suggestions applicable to e-commerce standardization. Category adjustment rules highlight the need for detailed classification management in policy formulation.

3. Business models: The platform's mutual trust mechanism and account credibility system innovate merchant relationships. A healthy environment fosters predictable growth, serving as a model for other industries.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

【亿邦原创】1月22日消息,日前,淘宝天猫发布了有关商品评价、销量特殊计算逻辑的通知。平台将通过明确的规则和平台排查,控制虚假交易为商家真实评分带来的影响。

根据新规则,符合以下任一情形的订单,销量均不累计,且对应评论内容将被屏蔽,且订单相关数据不计入商家评分:

1、针对单件商品最终成交价格显著偏离该商品正常售价区间,并进一步造成了商品销量虚高,虚增,误导消费者等情况。比如卖家通过修改价格、设置大额优惠等形式使得单件商品的支付价格低于一口价3折,且支付金额低于1元的订单销量删除不累计。

2、针对卖家通过修改、删除或新增SKU,导致商品核心信息发生实质性变更,从而成为另一款商品的部分历史成交订单,并进一步造成了商品销量虚高,虚增,误导消费者等情况。

3、基于大数据技术,平台排查认定为异常的订单。

同时,规则对实际支付金额低于1元订单,以及调整商品类目的情况也做出了限制。

以1元以下价格支付的订单,销量正常累计;若买家账号绑定有效手机,买卖双方评价正常累计,若买家账号未绑定有效手机,该类订单的卖家端评价至多累计250笔,买家端评价正常累计。

而除了平台官方类目调整外,任何商品调整类目:转入和转出特定一级类目的商品,近30天销量全部删除不累计;其余调整一级类目的,1元以下价格支付的订单销量全部删除不累计;从“个性定制/设计服务/DIY> 其它定制”末级类目调整到其余类目或从其余类目调入的,商品近30天销量全部删除不累计。

据悉,上述特定一级类目包括办公设备/耗材/相关服务、文具电教/文化用品/商务用品、个性定制/设计服务/DIY、网络设备/网络相关、五金/工具、手表、运动鞋new、住宅家具、家装主材、成人用品/情趣用品、计生用品。手机类目如从其余类目转入,删除销量。

亿邦动力了解到,过去几年,淘宝天猫一直致力于优化商家经营环境,先后取消仅退款、打击恶意羊毛党、治理恶意店群,还首创了账号诚信体系,并与商家建立起互信机制等。

而就在日前,淘宝天猫举行了商家服务大会,推出了售后AI假图识别模型、细分行业和场景争议处理规则等多项举措,计划通过好服务、好工具、好保障帮商家反内卷,帮商家在健康的经营环境中获得确定性增长。

亿邦持续追踪报道该情报,如想了解更多与本文相关信息,请扫码关注作者微信。

文章来源:亿邦动力

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