Disruptive innovation

The disruptive retail technology removing data blind spots

Jun 30, 2016

Ask any CEO who has invested big dollars in Big Data what they believe their ROI is, and nine out of ten will say 'not enough'.

For Australian retailers in particular, whose transaction data alone offers a treasury of customer insights, the challenge continues to be sorting the good from the bad – from the downright ugly data.

Cutting-edge data visualisation and mapping technology has changed the fortunes of many of the world’s data rich, information poor retailers. What this new breed of advanced analytics tools offer over the more traditional solutions is an ability to resolve data blind spots.

The most disabling blind spots harboured in traditional BI tools are caused by a lack of real-time data integration, limited or absent predictive capabilities, and the inability to clearly identify patterns and trends.

Location-based analytics technology addresses these blind spots by connecting data to the real-world and using geographic context to provide actionable business insights.

Starbucks has been successfully using location-based analytics to undertake market planning and store development in recent years, with the aim of ensuring their global network of 20,000 plus coffee outlets continues to grow responsibly.

Working on the principle that ‘one size does not fit all’, Starbucks has been able to ensure the success of its network expansion program.

Decisions around the location of new stores are determined by analysis of local trade areas, demographics, traffic and transport routes and new commercial developments.

Starbucks uses Geographic Information System (GIS) technology – which underpins advanced location-based analytics – to equip more than 700 of its mobile location scouts with the ability to conduct analysis in the field.

Intel is fed back into Starbucks’ market planning and BI systems instantly, saving on time and administrative costs.

Starbucks’ site selection activities are only a small component of the company’s highly-effective GIS technology deployment strategy.

Today Starbucks uses GIS technology to leverage the millions of data records captured each day for global safety and security planning, facilities management and the planning of new product roll-outs – such as the introduction of alcoholic beverages with their evening menus.

IBM estimates more than 2.5 quintillion bytes of data are created each day, with 90 per cent of data having been created in the last two years alone.

This figure won’t surprise many, with retailers’ loyalty, stock, online and point-of-sale data alone contributing to vast, almost unmanageable information reserves.

Using traditional data mining techniques to deal with Big Data is like trying to bag a quality bargain three days after the Boxing Day sales – most likely, you’ll expend a lot of time and energy and only walk out with other more diligent shoppers’ cast-offs.

The digital age is forcing retailers to leverage their Big Data in a more sophisticated manner. Consumers are determining what the customer experience needs to look like and smart retailers are keeping across these ever-changing preferences by mobilising advanced analytics.

GIS technology allows retailers to get ahead of the curve, to see patterns in consumer sentiment as they unfold.


By visualising these insights against a backdrop of trade territories, CEOs and BI professionals alike can instantly see a far greater return from their Big Data.

If you’d like to learn more, you can watch this video of Starbucks’ manager of strategy, Patrick O’Hagan, discussing how the company is successfully leveraging location-based analytics.