PDD(US:PDD) Sou Hu Cai Jing·2025-08-21 13:28Core 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]