Wouldn't it be nice if your repricing solution took into consideration the amount of money that your customers are willing to spend for products? Well, that is exactly what Feedvisor does.
This self-learning repricing solution has launched Version 2.0 of its software for Amazon Marketplace Sellers. The update improves on the solution's original algorithm by introducing machine learning technologies, as well as has added actionable analytics to the platform.
"This new version of our algorithm combines Big Data with machine learning. It looks at a much broader market environment and analyzes a considerably greater historical dataset than we've ever looked at before, to fine-tune prices and optimize profits," said Victor Rosenman, founder and CEO of Feedvisor. "Our platform uses a closed-loop, learning algorithm. This means that with every sale that goes through our client's account, continuous adjustments are being made that increase the accuracy of our solution for each specific product."
The Feedvisor platform is completely automated, and can be leveraged to help online marketplace sellers to grow their sales and outperform the competition. This is because the platform doesn't require sellers to set complicated pricing rules. Instead, the technology checks hundreds of competitive prices every hour and automatically sets prices based on numerous variables. That said, it is important to note that the pricing solution doesn't just set prices at the cheapest number, but at the price that customers are willing to spend. In fact, the platform can reduce time spent on price management by up to 90 percent.
The new version of Feedvisor also introduces a suite of actionable analytics and alerts that deliver real-time business insights and add transparency to the repricing process. This is because online marketplace sellers are now able to see which items are not selling, which are not priced competitively, what products have seen a spike in sales and which items will soon run out of stock.
