Kenny Lee

VP, PMDO

July 25, 2013

  • Share by Email
  • Tweet This
  • Share on Google+
  • Share on Facebook
  • Share on LinkedIn
  • Tweet This

2 Ways Big Data Helps Location Analytics

Opportunities for businesses to unfold key insights.

2ways

Big data presents a huge opportunity for businesses to unfold key insights by applying principles of statistics, mathematics, and artificial intelligence. We’ve all heard how Big data analytics can help discover hidden patterns and predict future scenarios that can help drive business decisions for developing innovative products, drive revenue growth, improve supply chain effectiveness, mitigate business risks, and enhance customer intimacy. But there are two big things that big data can do for businesses looking to improve their location analytics.

1 – It enables monitoring of events and embedding of insights into real-time decision-making.

What makes big data analytics really powerful is that in many cases it enables real-time decision-making. Just think about getting healthcare recommendations through analytics that calculate the probability of different diseases and recommended treatments, based upon doctors written text. Similarly, leading retailers have the potential to leverage real-time footfall analytics from mobile network events, Wi-Fi data, GPS coordinates, and other forms of geo-location big data to make personalized offers to customers as they travel to the store, and even while in it, based upon real time behaviors. Today city planners are experimenting with multiple forms of big data [i.e. machine to machine (M2M), street light sensors, and telematics sensors] to aid government organizations in building a real-time dynamic view of an urban population and optimize the security provisioning for the city. Utility providers are leveraging sensor data related analytics to understand how operations are performing and when to do predictive maintenance.

2 – It helps facilitate smarter store-selection decisions.

Location analytics software can help retailers can make smarter store-selection decisions, said Simon Thompson, director of commercial solutions for ESRI, a Redlands, Calif.-based developer of location analytics and map-based visualization software. Poor site selection is an ongoing problem for retailers. Rapid expansion was an ambitious, if sometimes misguided, strategy for many retail chains prior to the global recession of 2009. The end result was often “zombie” stores that were either unprofitable or underperforming. “When retail was growing by 6% to 8% per year, (retailers) believed that if you just plopped down a store, somehow it would be successful,” said Thompson in a phone interview with InformationWeek. “They were going for growth and scale,” he noted. “One of the things that occurred is that many of those stores never had was the sales or market potential to make them truly successful.”

According to Thompson, there are essentially two types of zombie stores: “The zombie stores which are essentially dead, like many of the malls in America. They’re in the wrong place, they’ve got the wrong tenants and they’re not relevant to the consumers’ expectations of today,” he said. “And then there are stores which are … on profit life support. They’re not doing anywhere near as well as they could.”

Location analytics may not be new, but it has the potential to offer businesses what Ventana Research CEO and chief analyst Mark Smith calls “location intelligence”, a combination of geographic context and maps with business intelligence applications. “Information about location or geography can improve the quality of actions, decisions and responses to opportunities, and enable organizations to understand more about their customers,” Smith wrote in a March 2013 article for Directions Magazine which covers geospatial technology.

According to an ESRI white paper on location analytics, the fusion of business intelligence (BI) and geographic information system (GIS) technology can help organizations visualize and analyze key information through “smart” maps. The goal is to discover patterns and trends that the organizations might have missed via conventional BI tables and charts. In addition to providing what Directions Media (publisher of Directions Magazine) editor-in-chief and vice publisher Joe Francica calls “an alternative method” to synthesize data, location analytics offers the potential to incorporate unstructured data types with geospatial information such as social media streams and sensor readings into business analysis.

OK, but how does all of this relate to the problem of zombie stores? Well, ESRI says its location analytic tools can help retailers avoid a formulaic approach to site selection and other pitfalls. “It’s geo-enrichment, having more information on top of the information that you have, using geography to connect that together,” said Thompson. “Companies are trying to integrate bricks and clicks, sales data, social media, searches — all of these components. That’s really driving interest in (ESRI) as a platform.” A great example of this is the reality TV show Bar Rescue, on Spike TV,  which uses ESRIi’s location analytics software to help bar owners save their failing businesses.

It’s important to note that not all underperforming stores need to be shuttered. “Sometimes it’s not necessarily moving your location,” Thompson noted. “It’s changing your focus in your location because you understand it better.”

Stay updated. Subscribe now to receive valuable insights each week from the web’s best blog on retail growth in Asia.