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How big data analytics is revolutionizing retail

Paul Newman Archive

As more executives in the retail sector discover the immense power of big data, there's a major change afoot in the industry's thought process. What's the best way for merchants to allocate their resources - should they work as diligently as possible to open more locations and sell more products in brick-and-mortar stores, or is it better to devote their limited space and manpower to data analysis?

A generation ago, retail was simpler, as more locations unequivocally meant more success. But in today's landscape, some executives are choosing to move their business to the e-commerce realm and reappropriate their physical real estate to build more data centers. Rather than focusing on serving customers in the flesh, executives are turning their attention to information mining, data quality and analytics.

Forbes reports that Sears is one such retailer making this change. A new subsidiary of the corporation plans to take more than 2,500 Sears and Kmart properties and convert them from stores to data storage facilities, equipping them with servers, chillers and backup generators.

Because Sears is struggling in its competition with bigger retail chains like Wal-Mart and Target, some creative thinking is needed for the company to revamp its business strategies become a viable threat to its rivals again. Opening a data center is likely to yield a greater ROI than maintaining a struggling store, so it might be worth the risk.

Dick Seesel, principal at Retailing In Focus, told Forbes that he was skeptical about the idea, as crunching more data might not ultimately help.

"This is the latest example of Sears Holdings management floating a 'big idea' to gain traction from its real estate portfolio," Sessel wrote. "Most of these ideas have not turned into reality, but they serve to distract [Sears] from the necessary task of investing in its actual brick-and-mortar stores. The quarterly losses and sales declines won't stop anytime soon with this scattershot approach."

Then again, if you're Sears, what do you have to lose? Companies must find ways to modernize their business strategies if they want to remain competitive, and opening more data centers might be their best chance.

Here are a few ways that big data analytics can help all retailers - whether they're struggling like Sears, or on top of their game like Target - improve their operations.

Analyzing store locations
This is especially challenging considering that many retailers are closing locations in order to focus on data. Corporations must use the information at their disposal to figure out how best to utilize their real estate - figuring out where store locations are likely to be successful, where they're not and when relocation might be necessary. By dissecting data clusters on their real estate holdings and the economic conditions of the surrounding communities, companies can make better decisions.

Optimizing prices
In order to remain competitive against richer business rivals, retailers must find the perfect price points - high enough to ensure a profit, but not so high that customers will be scared off. Big data can help executives fine-tune their pricing to find a happy medium and optimize their sales.

Making difficult staffing decisions
One of a retail chain's biggest expenses is labor. By using big data to analyze where employees are located and how much work they put in, retail executives can assess which locations are armed with too much manpower and which ones have not enough. Furthermore, data can help with difficult decisions about providing personnel during peak seasons, such as the holidays.

E-commerce has made it easier for retail chains to move away from physical locations and do more with their real estate. Storeroom shelves and checkout counters are on the way out, and data is on the rise.