The top 20 Internet retailers changed their prices 30 times more often than their peers who had lower sales during the holiday season in 2011, according to BlackLocus, a startup that helps companies set competitive prices online. That’s a lot of price changes and through examples like this the startup shows how data is a tool, much like electricity, plastic or broadband and how you use it will define your product.
BlackLocus uses it to create a dynamic pricing environment to help retailers stay nimble and respond to the current market. The Austin, Texas-based company raised $ 2.5 million in initial funding last summer, and aims to help online retailers of any size keep up with their competition through a mix of data mining and analysis. The end result will bring the same pricing transparency that tools like Google Product Search or Shopzilla have given consumers to online retailers.
Rodrigo Carvahlo, the CEO and founder of BlackLocus, explains that online retailers hire the company to help them track what competitors are charging for the same products. This sort of price comparison is hard to do at a massive scale, but BlackLocus’ success getting over the technical challenge, could pave the way for a future when retail prices could be set in real-time based on the retailer’s existing inventory, what other companies are charging and the overall demand threshold for the consumer.
For example, ahead of Christmas, I saw the FurReal Go Go My Walkin’ Pup on sale for prices that ranged between $ 45 and $ 65 online over a period of two weeks when I began eyeballing the toy as a gift for my daughter. I eventually picked it up for $ 45, after seeing it priced lower at Target.com than the current prices at Amazon or Toys R Us. Had I been more diligent I could have use a price tracking service like PriceProtectr, Google Product Search or just scanned a UPC code into Shopzilla or ShopSavvy while out and about to find the lowest price for that moment.
That kind of consumer transparency is what BlackLocus wants to bring for retailers when they are trying to set their prices. For a small online retailer being about to offer a similar or lower price than Amazon or Target could help keep them competitive. Similarly, if they saw that Amazon or Target were sold out, they might be able to raise their prices. But the problem of getting the data, matching it to the right products that might carry different names or SKUs online and then comparing the pricing all takes work.
The hardest part is matching the products across different sites said Carvahlo. To get the data, BlackLocus crawls online retail sites a few times a week, or as often as the prices tend to change (thanks to its knowledge about pricing, folks who work there know the absolute best time of year to buy televisions, or how many months a phone has to be one the market before the price drops). Once it has the pricing data it runs several algorithms against the data to match products across different sites and puts them in a database. It’s a significant amount of data and it’s growing rapidly. Robert Taylor the COO of the company emailed me to say:
We really look at [the data] two ways. First, the number of product URL’s (think product page) that we track and second, the price data cluster capacity. We are well on our way to tracking 150M product URLs, projected to be nearly 300M by the end of 2012. Similarly, our cluster capacity is nearing 9 TB over the next few months, significantly increasing to 125 TB by the end of 2012 as we store historical information. These types of increasing requirements really require us to constantly iterate on designing/deploying scalable infrastructure.
Like many startups, BlackLocus uses Amazon Web Services for some of its infrastructure and it’s planning on implementing a more enterprise data analytics product such as SAS to help it manage and analyze the prices. BlackLocus doesn’t disclose its customers, except to say that it has customers that range from those in the top 75 internet retailers to small mom and pop shops. So it’s not only mobile that’s changing the face of retailing, but data as well.
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