Optimizing Historical Sales Data Retrieval for Video Games and Consoles on eBay
I currently operate an eBay store primarily focused on trading cards, but I’m shifting my attention toward video games and gaming consoles. To support this transition, I’ve been developing a Python-based project that leverages the eBay API to create a database and provide price predictions for these products based on historical sales. e-zpassnj
However, I’ve run into a challenge when trying to retrieve accurate historical sales data. For example, when I query sales for popular Nintendo consoles, the results often include items with unrealistically high prices or listings that don’t reflect actual completed sales. This makes it difficult to generate reliable data for price analysis and predictions.
From what I’ve learned, one common issue is not filtering API requests properly. eBay provides options to filter by soldItemsOnly and condition (new or used), as well as specifying date ranges and categories. Applying these filters can significantly improve the accuracy of historical data. Additionally, it helps to cross-reference multiple endpoints and limit results to items with verified sales rather than just listed prices.
I’m looking for advice or strategies on refining API queries, cleaning outliers, and improving data quality so that the database can better reflect realistic trends in video game and console sales. Any insights on efficient techniques to achieve accurate historical sales records would be incredibly helpful.
