What Are the Best Amazon Product Analytics Tools?
True product innovation means solving a market need. Today, the Internet provides more data than ever before that can help product teams identify market needs.
That said, data is not the same as actionable insight, and data without meaningful analysis is just meaningless noise.
To take advantage of product data, particularly from massive sources like Amazon, product teams need to turn to special purpose analytics tools.
The best Amazon product analytics tools can collect and organize data on what products consumers are buying and how they are using them. The data is then used by product teams to make strategic decisions around what products should be produced, how they should be priced, to what market they should be sold, and more.
These tools provide insights into demand forecasting, competitor analysis, market research, and more. Another key feature is the ability to analyze large datasets quickly without sacrificing data quality.
Commerce.AI provides all these features, and more—powered by the world’s largest product data engine, which has scanned over a trillion data points from unstructured sources, including Amazon.
In addition to analyzing Amazon product data at scale, this data engine has scanned sources from Walmart to Target, uncovering a broad range of product insights.
This engine has been used by market leaders like Unilever, Suzuki, and Netgear to design more innovative products and features, that meet consumer needs and beat the competition.
With Commerce.AI’s 10,000 AI-generated market reports, you can gain a glimpse into the power of a massive data engine. These market reports include a summary for each product category, highlight the top brands, the top products, the number of products and reviews, and an opportunity meter, indicating the size of the market opportunity at hand.
While there are a number of tools useful for individual retailers, from SellerApp to Jungle Scout to AMZ Tracker, these tools fall short for product teams and large organizations looking for market insights.
AI versus Traditional Analytics
What once took countless hours of manual Amazon product analysis can now be done in minutes, thanks to Commerce.AI’s data engine.
Traditional analytics is extremely expensive, because it requires hands-on, human work. With the billions of product data points out there, no business has enough time or money to manually analyze all this data.
That means that traditional analytics comes with huge sacrifices. Businesses can’t analyze all product data, so they have to select and choose among limited sources, which yields limited insights.
This problem will only compound as Amazon’s growth continues to explode, and there’s more data out there than ever before.
At the same time, this means that product teams taking advantage of AI will have an ever-growing competitive advantage.