Big Data in the Physical World: Will It Trump Online Analytics?

Big Data in the Physical World: Will It Trump Online Analytics?

Summary: Big Data is typically associated with the online world, but where it may be biggest is in brick and mortar retail.


This guest post is from Tim Callan, CMO of RetailNext, a provider of real-time in-store monitoring and analytics.

By Tim Callan

  Online retailers have easy access to mountains of internal data gathered from users’ everyday actions (number of visits, page views, clicks, average time, etc.) and use them to optimize the shopping experience. Store analytics turned out to be a huge business in the e-commerce world, as exemplified by Adobe’s 2009 acquisition of Omniture for $1.8 billion and the presence of Google Analytics on nearly 50% of the world’s million most popular websites. The digital nature of e-commerce made these measurements straightforward from the get-go.

In the physical brick-and-mortar world, the engineering required to measure actual consumer behavior is much more challenging.  But new technology advances make it possible to extract more information from brick-and-mortar stores than ever before. The physical world is ripe for information gathering since its very nature ensures that the depth and richness of data is, in principle, unlimited.

Web sites are finite; physical stores are not For example, a typical e-commerce site has well under fifty links on any given page, equating to fewer than fifty actions you can take. But someone standing in a physical store with an item in hand has infinite possibilities for what to do next. She can walk to the register through endless possible paths. She can interact with any object in the store. She can speak with an employee on limitless topics.

So, can data gathered from physical stores trump online analytics in volume and depth? With sources such as the store’s point-of-sale (POS) systems, video feeds from ceiling cameras, staffing software, RFID tags and more, an in-store analytics installation can measure 10,000 data points per store visit.

Data in; insight out Advanced analytics in physical stores today can give retailers more information than ever before. In addition to those mentioned above, situational metrics also include:

  • Emotion: There is no “mood mouse” to tell if an online shopper is frustrated, confused, excited, or bored. In the near future, physical stores will be able to draw conclusions about shoppers’ emotions based on facial expression.
  • Location: E-tailers must treat all shoppers the same, at least per country. Brick-and-mortar retailers by their nature uncover the differences in shopping behavior based on location, even down to the street-by-street level.
  • Demographics: Are shoppers male or female? Old or young? Alone or in groups? With children in tow or without? All these factors change the shopping experience and purchasing decisions. Online retailers can’t answer these questions, but physical retailers can.

These analytics open up a host of deeper insights for store managers. For instance, retailers can “heat map” their stores, providing information on how much shoppers travel to specific parts of the store – from aisles to endcaps. Heat mapping helps retailers increase sales considerably by matching the location of the products they most want to sell with the most trafficked parts of the store.

Brick and mortar not Fleeting Adweek recently published an infographic about the distribution of e-tail sales, which found “online shopping could represent 20 percent of retail sales over the next decade.” Another way of expressing the same point is would be: A decade from today, brick-and-mortar shopping will represent at least 80 percent of retail sales.

With this kind of industry dominance, there is no room for brick-and-mortar retailers to have disadvantages over e-tailers, or for there to be an information gap between the two channels.

By 2013, will retailers know more about brick-and-mortar shoppers' behaviors and preferences than about those of online shoppers? Many already do.

Topics: Enterprise Software, Banking, CXO, Data Centers, Software

Andrew Brust

About Andrew Brust

Andrew J. Brust has worked in the software industry for 25 years as a developer, consultant, entrepreneur and CTO, specializing in application development, databases and business intelligence technology.

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  • This Bud is hosed

    WalMart has long been a TeraData customer, and a big fan of Big Data. Before you can step away from the cash register at your local WalMart, the analytics in Bentonville are already crunching on what you bought. They don't know who you are, but they know the store's inventory is now lighter by a pack of AA batteries, a can of WD-40, and a pound of bananas.

    This stuff also compares stores, so when one store in a metropolitan area suddenly started registering 17% more beer sales than any store around it, and an odd correlation between that and garden hoses, the store manager got a phone call to find out what was going on. Turns out an associate had been interrupted in a task, and had left a palette of beer in the garden department next to the hoses. It seems that guys coming in to buy a hose for their weekend "honey-do's" were picking up a sixpack on their way out.

    So a message went out to the rest of the stores in the region: get some beer out there next to the hoses. If you can react this fast -- and WalMart can -- you get to sell more beer.
    Robert Hahn