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Data and Dynamic Pricing - The Next Revolution in Online Retail

December 12, 2014. Retail pricing intelligence is the name of the game. Physical and Digital retailing giants present different strategies to win. Company X, parent corporation to TJ Maxx and Marshalls, employs 900 buyers, each intimately familiar with a specialized product niche - office chairs, sandals, cutting boards - and provides stores with desirable items that can be sold quickly, with wide profit margins. Digital behemoth Amazon derives much of their insight from their extensive and enviable database. So exhaustive are their data stores that they are able to lease access and a selling platform to thousands of retailers across the world. Very few of Amazon’s data streams are truly proprietary, but to have them all under one digital roof is unique and, obviously, highly valuable. Amazon’s model has enabled them, in the words of Wiser CEO Arie Shpanya, to present the customer with “the right product, at the right time, at the right price.”


Data sophistication gives retailers the luxury of truly dynamic pricing. By gaining workable insight from myriad data points, pricing decisions become an oil painting rather than a chainsaw sculpture. Smaller retailers have had to subsist for years on the data insight they could scrape together on their own. Many have succeeded in their own right, while others have been subsumed into Amazon’s hulking retail fiefdom. It seems natural to imagine that one day, access to incisive data will become more democratized. The question is, how will this occur? How does one go from a model of one giant, with all the data knowledge, to many merchants, all of whom have equal access to the same data?


Shpanya thinks he has the answer. Wiser is an example of a new kind of data company, providing actionable insight from mountains of consumer and pricing data. The company acts as both data provider and analyst, finding the pattern in the matrix for their retail customers. The end result could (will?) be a tidal shift in the way retailers of all sizes determine the prices they offer their customers.


The beauty of data is that it does not lead a business to one specific business model conclusion. Just look in the world of traditional retail at the difference between the aforementioned TJ Maxx, Macy’s, and Wal-Mart. All of these companies are in the same business, essentially, buying up goods in bulk and selling them for more to individuals. They also have access to much of the same industry insight, which has led them in three notably different directions. In the digital space, there are even fewer retail winners than in the world of brick and mortar. The sphere is much younger also, and one can be sure that recent history will not repeat itself. Once Data is accessible, smaller retailers will be able to draw unforeseen conclusions from it and conduct truly insightful pricing analysis. At the very least, democratic access to big data, and the ability to draw insight from it, will result in a diversified marketplace with more fluid pricing than is presently seen.

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