Unveiling the Art of Product Selection: Five Methods based on product data for Amazon Sellers


In the dynamic world of e-commerce, selecting the right products can be the key to success for Amazon sellers. In this post, we will explore various methods for product selection, taking a micro view and conducting a case study by integrating data from popular products on Amazon. By applying carefully crafted filters and conditions, sellers can discover products with untapped potential, ensuring a strategic approach to market entry and growth.

Selecting Products Based on Potential:

The best potential market is a market with high demand and low competition. But identifying such a market would be too idealistic. So, on the other hand, we can filter out potential stocks that are not currently too explosive but have potential for future growth.
Filter criteria: Set monthly sold units to be less than 600, monthly sales growth rate to be greater than 10%, and shelf life to be in the past six months. At present, monthly sales are not too large but are in a growing trend. A short shelf life means that new products can also enter the market in the short term, suitable for small and medium-sized trading sellers.

Selecting Products Based on Product Maturity:

For factory-type sellers with strong production capabilities, a focused approach to their existing categories is recommended by combining the analysis of comments from SellerSprite for detailed analysis. Based on product maturity, including details such as material, size, color, style, etc., identify areas for improvement, fully understand the quality status of the product and buyer demands, and then upgrade and list the product or make differentiation in product details.

Filter criteria: monthly sold units>1000, star rating<3.7. This type of product has good overall sales but poor ratings, indicating that there is some room for improvement in the product.

Selecting Products Based on After-Sales Costs
This type of product has a certain sales volume, but its ranking is not too high and it is not easy to be targeted by other sellers. And with a high rating and fewer Q&A questions, it indicates that the product is simple and easy to operate, and there are fewer after-sales issues. Suitable for sellers who shop extensively or meticulously.
Filter criteria: monthly sold unitss>1000, parent BSR ranking in the range of 5000-10000, star rating>4.0, Q&A<5, can filter out products with good sales and low after-sales costs.

Selecting Products Based on Speculative Markets:

For some new stores without traffic or even shopping carts, following sales can also be a good way to attract traffic. A skinny camel is bigger than a horse, and even if there are multiple co sellers, it can still be profitable with high sales.
Filter criteria: monthly sold units>1000, number of sellers>3. Generally speaking, products under Amazon's brand, copyright, or patent cannot be co sold. This condition can preliminarily filter out products that have good sales in a certain category and are allowed to be co sold.

Selecting Products Based on Small Profits and High Sales:
Low priced products have lower capital requirements, lower trial and error costs, and relatively lower risks. But at the same time, sufficient sales support is needed to earn substantial profits. With fewer ratings, the marketing costs required in the early stages are lower, making it easier for new sellers to catch up or surpass.
Filter criteria: monthly sold units>3000, number of ratings<100, price<$10.

In the ever-evolving landscape of e-commerce, selecting the right products is a nuanced art. By employing these strategic approaches and applying precise filters, sellers can uncover hidden opportunities, minimize risks, and position themselves for success in the competitive world of Amazon.

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