The Next Big Thing in Customer Centricity is Already Here...Are You Taking Advantage?

Imagine yourself a retailing executive. Most likely you want to improve your understanding of actual customer behavior so that you could develop better inventory, marketing, and merchandising programs. What if your firm had the ability to track real consumer behavior across multiple locations, ranging from where they come from, to their buying habits and through to why they made specific transactions? That would be very powerful – and soon a common occurrence thanks to the emerging field of location analytics.\

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Simply put, LA collects, aggregates and analyzes a person’s credit card and GPS-device activity (e.g., interacting through social networking sites) to find relationships between place and action on their shopping and purchasing behavior. LA’s uniqueness traces to its ability to mine insights between the interplay of unstructured data like physical location, geographic context, behavioral activities and social habits. The power of LA is further magnified when it can overlay these location-centered insights with structured data found in existing databases like the census, internal CRM information and traditional geospatial technology that collects static information on roads, homes, etc.

A quintessential Big Data application, LA uses sophisticated algorithms, high performance computing, analytical capabilities and multiple data sources to identify hidden consumer and population patterns that can aid decision making and planning. A number of industries like retailing, real estate development, retail banking, and service firms are beginning to use LA to significantly improve marketing program effectiveness, enhance customer satisfaction and right size operations. This compelling value proposition plus the intersection of business and technology developments is spawning a rapid growth in the market. According to ABI Research, the LA market is forecasted to be $9B by 2016. Unsurprisingly, some of the world’s biggest IT firms including Microsoft, Apple, Facebook and Cisco have recently bought stakes in some leading LA providers.

There are many potential applications for LA services. Within a large mall, retailers can understand what items were bought, where and when; why the purchases happened in certain stores; and how the transactions were executed. More importantly, firms can understand the relationship between these variables in order to get a complete picture of aggregated consumer behavior at the mall. For example, where do shoppers and non-shoppers come from? Why do some consumers go to one store first? Or, why do people neglect to purchase from a particular store?

Consider another scenario. A restaurant chain wants to open a dozen more outlets across Canada. This strategy requires a significant amount of capital and effort while carrying substantial business risk. Using LA services can help management understand the relationship between demographics, traffic flows, local eating habits, psychographics, costs and income levels on potential site revenue and build-out costs. As well, the insights generated by LA would help determine the optimal food mix, service levels and store size for each location.

Despite its Orwellian undertones, LA is about helping companies track aggregate patterns and predict trends so they could make better decisions; tracking individual behavior has little business value by itself. Of course, firms will need to ensure there are adequate privacy safeguards and opt-out procedures to maintain consumer trust.

To fully exploit its potential, managers must ensure their LA technology and people investments are aligned to corporate goals and strategies. As with other Big Data projects, implementing LA initiatives will come with IT and organizational challenges that should not be underestimated. Before jumping in, companies will need to build out internal LA skills so that they can ask the right analytical questions, manage the data and capitalize on the learnings. Since organizations differ around their scale, IT and business needs, few enterprises (except large firms such as Walmart, McDonalds or Starbucks) would be advised to operate their own LA platforms. As a result, the market is seeing the emergence of information aggregators or data brokers like IBM who can consolidate and filter data from disparate sources and geographies by sector.

Mitchell Osak is managing director of Quanta Consulting Inc. Quanta has delivered a variety of winning strategy and organizational transformation consulting and educational solutions to global Fortune 1000 organizations. Mitchell can be reached at mosak@quantaconsulting.com