Whether you’re an Amazon seller who’s already using a repricing tool, or still searching for a repricer, it’s key to fully understand all the options available on the market so that you can make an informed decision.
Choosing a repricer that fits the needs of your Amazon business can mean the difference between winning the Buy Box or not, and turning a profit or not. So what the pros and cons of rule-based and algorithmic repricing? Each one of these has its own unique strengths and weaknesses. Here, we’ll walk you through them.
Rule-based repricing changes the seller’s item price in response to his or her competitors. Different predefined rules can be applied, with the ultimate goal of having the lowest price (e.g., match lowest price, beat the competition by a certain amount, and so on).
Algorithmic repricing applies computer algorithms to set the ideal price based on all known market conditions. It analyzes a wide variety of metrics—not just competitors’ prices—that affect the seller’s chances of winning the Buy Box.
Recommended for: Larger Amazon businesses with a wide range of products and complex needs.
For high-volume sellers, there are multiple proven benefits of using an algorithmic repricer. According to a study conducted by Northeastern University, sellers who use an algorithmic repricer perform better than those who don’t. While only 2-10% of Amazon businesses use an algorithmic repricer, algo-sellers compose one-third of best-selling products by third-party Amazon sellers.
Furthermore, the same study found that 60% of algo-sellers set prices that are above the lowest for a specific product. In other words, they are more likely to price higher without compromising on their share of the Buy Box or profit margins.
Michael Ward, an Amazon power seller and Inc. 500 award winner, credits much of his success to using an algorithmic repricer. He describes a popular item that he, along with 40 other sellers, were trying to sell: a tiara from the Disney movie Frozen. The stiff competition led to many sellers driving their price to the ground in effort to undercut the competitors.
He says that normally, he would have just set the price for $14.99 and let it run. But Feedvisor’s repricer allowed him to sell out within three days, for an average of $18 per item. He maximized his profit and sold all his stock, which is exactly what all sellers are aiming for.
Algorithmic repricers have an edge over rule-based repricing because their self-learning and data-driven algorithms are capable of evaluating the full range of seller performance metrics that Amazon uses to determine who wins the Buy Box. Unlike rule-based repricing, which tends to lower your prices even when you don’t have to, algorithms optimize for your end goal: bringing in a higher profit margin.
This article is written and contributed by Feedvisor. Feedvisor.com is the pioneer of Algo-Commerce – the discipline of using Big Data and Machine. Learning Algorithms to make business-critical decisions for online retailers. Feedvisor’s cloud- based Algorithmic Repricing and Revenue Intelligence solutions power millions of pricing decisions daily; providing retailers with actionable insights to maximize profitability and drive their business growth.