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How To Use Google Trends For Amazon Product Selection?

Product selection for Amazon Sellers is very important, and the selection tools are also varied. The Google Trends introduced in this article is one of the free tools provided by Google. So how to use Google Trends for production selection?

What is Google Trends?

Google Trends is Google's search-based product that analyzes Google's billions of search results worldwide and tells users how often a search keyword was searched for Google at various times. Simply put, we can see what people are interested in on the web through Google Trends.

How does Google Trends help Amazon Product Selection?

The ultimate goal of the selection is to meet the needs of the customer. However the most difficult part is to select specific product. We may be able to learn about the hot products through news, or through your friends. But when you heard that,  it is already the hot listings created by others sellers. so the important thing to remember is to know the trends, predict and take action before other sellers. Google Trends can provide complete and real-time data for our reference.

For example, search for precise keywords: Christmas lights and Christmas led lights

Through the chart above, you can see the trend of the search for these two keywords over time. It is clear that between the end of November and the beginning of December, these two keywords reached the peak, so we learned that Americans bought Christmas lights at this time, instead of waiting until Christmas is approaching.

With the trends, we can also know when to start preparing products, shelves, operations, advertising, and which of the most important keywords should be used, rather than rushing to prepare goods after others sellers.

Related queries 

you can also use Google Trends to find keywords and CPC keywords.

There are many ways to choose products, and no one can rely on one. Sellers should constantly integrate the strengths of each tools in practice to develop the most suitable method or tools combinations for production selection.