From “Making Business Easy for Everyone” to “Making Business Impossible for Fraudulent Sellers”: The Evolution and Challenges of Business Integrity

Problem Analysis: The Changing Business Environment and the Crisis of Integrity

In 2003, when Alibaba put forward the slogan “Making Business Easy for Everyone”, its core idea was to lower the business threshold through Internet technology and help small and medium-sized enterprises solve problems such as information asymmetry and limited channels. However, with the booming development of e-commerce, a new “cancer” in business has gradually emerged – brush orders.

Brush orders refer to artificially creating the sales volume and positive reviews of products or stores through means such as fake transactions and fake reviews to deceive consumers and platform algorithms. This behavior not only distorts market competition but also seriously damages consumers’ rights and the platform’s reputation. The shift from “Making Business Easy for Everyone” to “Making Business Impossible for Fraudulent Sellers” reflects a profound transformation of the business environment from “facilitation” to “standardization” and reveals the severity of the business integrity issue.

Why has brush orders become a widespread phenomenon? The root causes lie in the following aspects:
1. Vulnerabilities in platform algorithms: The ranking and recommendation mechanisms of many e-commerce platforms overly rely on sales volume and positive review rates, providing opportunities for brush orders.
2. Short-sighted behavior of merchants: Some merchants take risks in order to quickly increase their sales volume and rankings.
3. Laggard supervision: Legal and technological means have failed to keep up with the evolution of brush order behavior in a timely manner.

Solution: How to Build a Business Ecosystem Free of Brush Orders

1. Technological Means: Using AI and Big Data to Combat Brush Orders

• Behavior analysis: By analyzing users’ browsing, clicking, purchasing and other behavior data, abnormal transaction patterns can be identified. For example, a large number of orders from the same IP address within a short period of time and concentrated purchases by newly registered accounts.
• Machine learning models: Train models to identify the language features of fake reviews, such as templated and exaggerated wordings.
• Blockchain technology: Utilize the immutability of blockchain to record the authenticity of transactions and reviews.

2. Platform Rules: Optimizing Algorithms and Incentive Mechanisms

• De-sales-based ranking: Reduce the weight of sales volume in search rankings and increase more objective indicators such as product quality, service scores, and repurchase rates.
• Dynamic scoring mechanism: Conduct dynamic monitoring on products with abnormally high sales volume or reviews. Once problems are found, their rankings will be downgraded or they will be removed from the shelves immediately.
• Reporting reward mechanism: Encourage consumers and merchants to report brush order behavior and reward the reporters.

3. Laws and Supervision: Strengthening Punishment

• Clarify legal responsibilities: Incorporate brush order behavior into the legal category and clarify its illegal nature. For example, China’s E-commerce Law has clearly stipulated that brush orders are illegal.
• Cross-platform cooperation: Establish an industry blacklist. Once a fraudulent seller is investigated and punished by one platform, other platforms should also ban them synchronously.
• Credit punishment: Incorporate brush order behavior into personal or corporate credit records, affecting their commercial activities such as loans and bidding.

4. Consumer Education: Improving Discrimination Ability

• Identifying the authenticity of reviews: Educate consumers on how to distinguish fake reviews, such as paying attention to the detailed descriptions and time distribution of reviews.
• Guiding rational consumption: Encourage consumers not to blindly pursue sales volume and positive reviews but to focus on the actual quality of products and after-sales services.

Case Study: Alibaba’s Practice in Combating Brush Orders

As a leading enterprise in China’s e-commerce industry, Alibaba’s practice in combating brush orders is of typical significance. The following are some of the measures it has taken:

1. The “Risk Control Brain” system:

   • Alibaba’s self-developed “Risk Control Brain” system can monitor transaction behavior on the platform in real-time through big data analysis and machine learning. The system processes more than 10 billion risk detections every day and identifies a large number of brush order behaviors.
   • For example, the system will detect that in the orders of a certain store, a large number of buyer accounts are newly registered, and the delivery addresses are vague or repeated. These will be marked as high-risk transactions.

2. The “Integrity Mechanism” and “Merchant Hierarchy”:

   • Alibaba has established a merchant integrity file and incorporated merchants’ historical behaviors (including whether they are involved in brush orders) into the scoring system. Merchants with high integrity scores will receive more traffic support, while those with low scores will be restricted.
   • Through the “Merchant Hierarchy” mechanism, resources are tilted towards merchants that truly provide high-quality products and services rather than those that rely on brush orders to rise.

3. The Use of Legal Means:

   • Alibaba has cooperated with the police to crack down on many large-scale brush order gangs. For example, in 2016, Alibaba assisted the police in taking down a brush order platform called “Shatuinet” with an involved amount of more than 100 million yuan, and its founder was sentenced to imprisonment.
   • These cases not only deter fraudulent sellers but also convey the platform’s firm determination to combat brush orders to the whole society.

4. Consumer Participation:

   • Alibaba has launched an activity of “Rewarding for Reporting Brush Orders” to encourage consumers and merchants to report brush order behavior. Once the report is verified, the reporter can receive cash rewards or platform coupons.
   • In this way, the platform mobilizes the power of a large number of users to form an atmosphere of public supervision.

Conclusion: Business Integrity is the Core of Future Competitiveness

The shift from “Making Business Easy for Everyone” to “Making Business Impossible for Fraudulent Sellers” is not only a change in business slogans but also a sublimation of business values. In the Internet era, the transparency of information and the value of integrity have been infinitely magnified. Although brush orders may bring short-term benefits, in the long run, they damage the healthy development of the entire business ecosystem.

In future business competition, it is no longer about the competition for traffic but about integrity and user experience. Only those merchants that truly focus on users and adhere to honest business operations can remain invincible in the fierce market competition. Platforms, merchants, consumers, and regulatory agencies need to work together to build a fair, transparent, and honest business environment, which is the ultimate goal of “Making Business Easy for Everyone”.

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