Big Data in Retailing

Integrated online and offline experiments

According to some estimates, Walmart collects around 2.5 petabytes (1 petabyte = 1,000,000 gigabytes) of information every hour about transactions, customer behavior, location and devices. An IT analyst firm Gartner estimates that there will be 20 Billion (13.5 Billion in the consumer sector) devices connected in the “Internet of Things”. Imagine the amount of data that will be generated by these devices. Imagine a day where online and offline retailing data provide a complete view of customer buying behavior, and even better if the data is linked at the level of the individual customer to enable “true” customer lifetime value calculations.

Sources of big data in retailing

There is potential to exploit the vast flows of information in a five-dimensional space, across customers, products, time, geo-spatial location, and channel.

  • First, this information may be available now for hundreds of thousands of SKUs in the store, making the data set about products have a lot of rows in it.
  • Second, the amount of information about each product need not be limited now to a small set of attributes thus increasing the column-width, if you will, about the product information matrix.
  • understanding, tracking and mapping the customer journey across touch-points,
  • evaluating profit impact,
  • and better allocating marketing budgets to channel, among others.



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David BECK

David BECK

David is a former entrepreneur — Teacher — Researcher — Contributor to government publications.