The best Amazon keyword tracker is the one you own, fueled by data from Amazon’s API
You can now access keyword-level catalog data directly from Amazon APIs delivered to a private, trusted cloud warehouse or data lake you own. Choose industry leaders like Amazon Redshift, Google BigQuery, Snowflake, Databricks, Azure Data Lake, and Amazon Athena to store your data privately.
How Does The Amazon Catalog Keyword Tracker Work?
Unlike most keyword trackers, the data is direct from Amazon’s API. This means Amazon will tell you how it aligns the keyword you supplied to its catalog. This is Amazon saying, “This is how our system maps our catalog of products to a keyword.”
As a result, the keyword-to-product catalog offers authoritative linkages directly from Amazon about how a keyword aligns with its systems.
Amazon Catalog API vs Screenscraping
When comparing data sourced directly from Amazon APIs to data obtained through paths, typically screen scraping bots, several key differences emerge, impacting trustworthiness, usability, and strategic value.
Here’s a breakdown of these differences:
- Authoritative: Data sourced directly from Amazon’s APIs is typically more accurate and reliable because it is provided by the platform. The APIs are designed to give developers, sellers, and vendors access to the most current and precise information about products, sales, and customer interactions.
- Documented: The data provided through APIs is structured, well-documented, and designed for integration with existing systems and applications. Sellers and vendors have clear guidelines for interpreting and using the data. There is no mystery about how the data is sourced or the context of how it can be used.
For sellers and vendors prioritizing strategic decision-making based on reliable, compliant, and actionable insights, data from Amazon’s APIs represents a superior choice. It ensures adherence to legal and platform guidelines and provides a foundation for making informed decisions that can enhance competitive positioning and operational efficiency, given you know how the data is sourced and packaged.
Types Of Amazon Catalog Keyword Data Analysis
With data in hand, here are three types of data analysis that can be particularly impactful, along with reasons why sellers and vendors should care:
1. Keyword Optimization and Product Visibility Analysis
- Description: By examining the relationship between products and their associated keywords, especially in the summaries and sales rank files, sellers can identify which keywords drive visibility and sales. Analysis can include identifying high-performing keywords, understanding keyword search frequency, and correlating specific keywords with sales performance.
- Why It Matters: Keywords are the bridge between customers and products. Optimizing product listings with the right keywords can significantly enhance visibility, making products more likely to be discovered by potential buyers. This analysis can reveal gaps in keyword strategies, highlight opportunities to target less competitive keywords, and refine product titles, descriptions, and backend search terms for better search alignment.
2. Competitive Analysis and Market Positioning
- Description: Utilizing vendor details, sales ranks, and product type data, vendors can conduct a thorough competitive analysis. This involves assessing which products (and, by extension, which sellers/vendors) dominate specific keyword categories, understanding the competitive landscape for various product types, and evaluating how competitors’ products are ranked and reviewed.
- Why It Matters: In a marketplace as crowded as Amazon, understanding your competition is key to carving out a niche or maintaining a competitive edge. This analysis can inform sellers and vendors about where they stand with their competitors, identify high-demand but low-competition niches, and help strategize pricing, promotions, and product development to capture more market share.
3. Customer Preference and Trend Analysis
- Description: By analyzing product summaries, including average ratings, review counts, and dimensions, along with sales rank data, sellers can gauge customer preferences and emerging trends. This analysis can reveal what product features or attributes (e.g., size, type, utility) customers favor and how these preferences change over time.
- Why It Matters: Staying ahead or quickly adapting to customer preferences and trends is crucial for long-term success. Sellers and vendors can use this analysis to make informed decisions about product assortment adjustments, design improvements, and inventory management. Understanding customer preferences can also guide marketing strategies, allowing sellers to highlight product features most appealing to their target market.
For Amazon Sellers and Vendors, leveraging Amazon Product Catalog Keyword Tracker data for these analyses can provide insights to optimize listings, understand competitive dynamics, and align products with customer preferences.
This strategic approach enhances product discoverability and sales potential and helps make informed decisions regarding product development, marketing strategies, and inventory planning.
Get Started Automating Amazon Catalog Keyword Tracker Data — For Free.
The Amazon Catalog Keyword Tracker data offers a goldmine of opportunities for data analysis, which can be leveraged by Amazon Sellers and Vendors to refine their strategies, enhance product visibility, and ultimately drive sales.
Take control and own your keyword data. Ditch the bots and screen scrapers for code-free automation access to Amazon API product keyword data. Openbridge integration is a code-free, fully automated API integration.
Sign up for a 30-day free trial of our Amazon Catalog Keyword Tracker code-free automation.
References
Amazon Catalog Keyword Tracker | Openbridge Help Center
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