Amazon product data collection: comparison and application of manual and automated tools

Collecting product data on the Amazon platform is an important business activity, which can help operators better understand market dynamics, competitor situations, and user needs. This article will introduce two main collection methods: manual collection and third-party crawler tool collection, and discuss their application scenarios, advantages and disadvantages.

Manual collection

Manual collection is one of the most basic and direct methods. Operators can obtain the required information directly from the Amazon platform through a simple “copy and paste” action. This method is suitable for collecting Amazon search exposure page data and product detail page data. Although manual collection does not require special technology and is highly flexible, it has obvious efficiency problems. Taking a typical working day as an example, assuming that the operator can devote about 45 minutes to data collection every day, a maximum of about 540 data points can be processed in a day (if each product needs to collect three information: the number of reviews, ranking and price) , which is equivalent to 180 products). In order to improve efficiency, operators can reduce unnecessary dimensions by clarifying the purpose of collection or adopt sampling methods for data analysis.

Strategies for improving efficiency

• Clear goals: Focus on key indicators such as sales rankings, rather than comprehensive coverage; reduce the frequency appropriately because some data do not change much.
• Sampling method: For example, when studying the characteristics of products on the first 100 pages under a specific keyword, you can select a number of products at fixed positions on each page for inspection to reduce the workload.

Collection by third-party crawler tools

For businesses that want to obtain data more efficiently, third-party crawler tools are an ideal choice. This type of software, such as Octopus Collector and Houyi Collector, can realize automated and large-scale information capture, and is especially suitable for data sets that require long-term monitoring. While the technical barriers to entry for using these tools are relatively low, they offer significant time-saving advantages. It’s worth noting that using such tools may involve subsequent data cleaning work, and some advanced features may incur fees.

Practical examples

Taking the ivy collector as an example, you first need to download and install the software. Next, create a custom collection task, enter the target web address (such as Amazon search results page), and configure relevant parameters. Through simple interface operations, you can specify the required fields (such as the number of reviews, links, etc.), and set up a page turning mechanism to capture more page data. In addition, specific information on secondary pages (such as parent ASIN) can be further extracted through XPath technology.

Notes

• When performing long-term tasks, it is recommended to schedule the crawler to run during non-working hours to avoid interfering with daily work.
• Considering that frequent access may lead to the risk of IP being blocked, when using crawler tools, requests should be dispersed as much as possible and avoid using network environments related to store management.

In summary, both manual and automated methods have their own applicable scenarios and limitations. Operators should weigh the pros and cons based on actual needs and choose the solution that best suits them.