What Separates Repricers from High-Quality Price-Data Providers?

BURLINGTON, Mass. - Jan. 20, 2020 - PRLog -- Customers often ask us how our pricing solutions are different than repricers. There are indeed many in the market that just offer repricing — a quick Google search will yield a flood of them.

An auto-repricer can provide alerts on competitors' pricing in comparison to your business, and allow you to reprice based on rules that you set. For operating on Amazon, that may be a fine solution. There, data is standardized and each SKU has an ASIN. However, once you operate outside of Amazon, the equation changes.

As a customer, if I am purchasing Levi's bootcut jeans in a medium-size, I compare the price on Nordstrom against Neiman Marcus. I don't compare a size L with an M. If you are Bloomingdale's, you must compare products you sell with a competitor in the same cluster as yourself for the hundreds of thousands of SKUs you sell.

It is extremely hard to precisely pinpoint the products your competitor sells that directly compete with yours using a repricer. Something as insignificant as the minor details within a photo can complicate the comparison. The title will generally be different, too, as each retailer adds its spin to the way it describes the product.

A standard repricer cannot accurately tell you what a competitor is selling because:

• Algorithms cannot yet guarantee with 100% certainty that the apparel products that you are seeing on a competitor's site are the same as your product. You need trained humans who understand the subtleties of fashion to pinpoint the product your competitor sells that is identical to yours. Only with this human intelligence and intervention can you confidently establish the price of your competitor versus yourself. A standard repricer cannot think like a human. We have seen retailers having to hire analysts to verify the repricer's data, thus adding to the cost.
• You encounter many problems when you try to read repricer data. It is extremely hard to engineer consistent reliability into all of the numbers. Hence, again, your internal team is forced to manually review and verify this.

If you are a U.S. store like Bloomingdale's, you primarily compete in a space with retailers like Nordstrom, Neiman Marcus, Lord & Taylor, Macy's, and others. Meaning that most of your direct competitors are likely going to be in the same cluster matrix (https://growbydata.com/top-5-methods-for-doing-dynamic-re...) as yourself.