Core Viewpoint - The article discusses the shift from traditional API interfaces to RPA (Robotic Process Automation) tools for data acquisition in e-commerce, particularly in the context of Pinduoduo's recent changes to API access. It highlights the technical workings of RPA and its advantages over traditional methods. Group 1: Limitations of Traditional API Interfaces - Traditional API interfaces are limited by the platform's willingness to maintain and open these channels, leading to potential disruptions in data access [3] - The scope of data obtainable through APIs is often restricted, limiting access to basic metrics while excluding richer consumer insights that are crucial for businesses [3] Group 2: Working Principles of RPA Technology - RPA technology operates by simulating human actions to gather data, functioning like "digital employees" that can work continuously and efficiently [4] - RPA tools can adapt to changes in platform layouts using computer vision and machine learning, maintaining data extraction capabilities despite interface modifications [4][5] - Advanced RPA tools possess self-learning capabilities, allowing them to adjust to minor changes in page structure automatically, thus ensuring uninterrupted data acquisition [5] Group 3: Technical Implementation of Data Extraction Tools - The "Qushubao" tool exemplifies RPA technology, optimized for e-commerce with over 100 pre-set data connectors for Pinduoduo, covering various data fields [7] - This tool allows for seamless data integration without the need for API access, making it user-friendly for non-technical personnel [7] Group 4: Data Security and Compliance - RPA tools reduce data leakage risks by keeping data within the merchant's control during the extraction process, unlike traditional APIs that may expose data to vulnerabilities [8] - The data extraction process adheres to compliance regulations by only accessing the merchant's own data, avoiding sensitive platform information [8] Group 5: Technical Challenges and Solutions in RPA - RPA faces challenges such as CAPTCHA recognition, which can hinder automated processes, but modern tools have integrated solutions for this issue [11] - Speed control is necessary to avoid triggering platform security mechanisms, with RPA tools simulating human-like operation speeds to mitigate detection risks [11] - RPA tools are designed to handle network instability, allowing for task continuation from the last point of interruption, enhancing reliability for long-duration tasks [11] Group 6: Future Directions - The article concludes that the evolution of data acquisition technologies will continue, driven by advancements in artificial intelligence, machine learning, and natural language processing [13] - The best technologies will seamlessly integrate into business processes, addressing real-world challenges effectively [13]

Core Insights - Pinduoduo's closure of API access for mainstream ERP systems has forced traditional merchants to seek new methods for efficiently obtaining operational data [1][3] - The article discusses the technical pathways for data acquisition and how merchants can adapt to the loss of API dependency for long-term, stable, and efficient data retrieval [1] Group 1: Challenges Faced by Traditional Merchants - The first major challenge is a drastic decline in order processing efficiency, with order data now taking over 30 minutes to download, far exceeding the platform's requirement of under 5 minutes, leading to a 40% reduction in overall operational efficiency [3] - The second challenge is a significant increase in inventory synchronization errors, with manual methods resulting in a ±15% error rate compared to Pinduoduo's requirement of ±3%, causing issues like overselling and stockouts [3] - The third challenge is a noticeable delay in after-sales response times, which exceed 6 hours compared to the platform's requirement of under 90 minutes, negatively impacting customer satisfaction and store ratings [3] Group 2: Evolution of Data Acquisition Technology - Before the prevalence of API interfaces, e-commerce data acquisition evolved from manual data export to automated solutions via APIs, which allowed structured data exchange between systems [5] - API interfaces, while efficient, have limitations such as requiring specific permissions from the platform and being susceptible to interruptions if the platform makes adjustments [5] - Additionally, API interfaces often restrict the range and format of data available, limiting merchants' access to comprehensive consumer insights [5] Group 3: Breakthrough in Simulating Manual Operations - A new data acquisition solution has emerged that simulates manual operations to gather data without relying on official APIs, utilizing technologies like RPA (Robotic Process Automation) [6] - For instance, the tool "Qushuitan" automates the process of logging into Pinduoduo's merchant backend, locating sales data, and performing data selection and download tasks [6] - This technology allows for seamless data integration and covers over 100 high-frequency data pages, enabling merchants to efficiently gather comprehensive data without development needs [6] Group 4: Efficiency Comparison in Practical Applications - A case study from a home goods store illustrates that before using the automated solution, staff spent hours manually collecting and organizing data, severely impacting order processing and inventory updates [8][9] - After implementing the automated tool, data collection and initial organization tasks were completed in minutes, significantly enhancing overall operational efficiency [9] Group 5: Economic Implications of Technology Application - Labor costs are a significant component of operational expenses for merchants, with traditional methods requiring at least two employees dedicated to data collection, costing around 10,000 yuan per month [11] - The automated tool reduces the need for manual labor, leading to substantial savings in labor costs and minimizing errors associated with human data handling [11] - By eliminating repetitive tasks, the tool also helps prevent costly mistakes that could arise from data entry errors, thereby protecting merchants from potential financial losses [11] Conclusion - The essence of technology is to serve businesses, and when one path is blocked, new avenues will emerge [12] - In the e-commerce sector, data is a vital resource, and the ability to acquire data remains a core competitive advantage for companies [12]