Amidst the meltdowns of Sears, Toys-R-Us and Brookstone, formerly online-only startups like Casper, Warby Parker and UntuckIt are quickly expanding into the thousands of empty spaces left behind.  And at the same time, tech giants like Amazon are moving into retail while another tech giant, Microsoft, is partnering with Kroger.

Clearly, the death of retail has been greatly exaggerated.  And the impact of technology on retail is only just beginning to be understood.  For organizations with the expertise, Artificial Intelligence, more specifically the use of data for machine learning, is starting to have a profound impact on retail.

AI is improving customer engagement, productivity, and efficiency throughout the supply chain as well as helping retailers design better stores and merchandise their products.

Customer Satisfaction

Far too often, the use-case cited by retailers for personalizing experiences is to offer some sort of discount only because “we know you”.  As location-based marketing via smartphones matured, the classic example was “customer walks by a coffee shop, offer them a discount”.  And why isn’t this a great example?  It’s expensive.  Margins are squeezed enough already, cutting prices further only makes it worse.

A better approach is to use available data to improve customer satisfaction by providing a more relevant experience, and hopefully reducing churn at the same time.  The overwhelming number of channels and mediums for connecting with consumers can be daunting to humans, but not for machines, which can use past data to understand where customers prefer to engage with your brand.  This applies to both customer service and targeted recommendations.

Behavioral Analytics

Customer data also doesn’t necessarily have to identify information related to purchases.  It can also be anonymized data about what customers do in stores.  Retailers have been tracking us for some time, but it’s either been through following the unique identifiers in our mobile phones or using facial recognition from surveillance cameras.  The Beacon Boom (and bust) of 2013 was supposed to usher in a new era of in-store tracking and messaging, though reality never met the expectations.

Vendors, such as Vayyar, are using radio waves (similar to motion detectors and police radar) to track people’s movements and actions with very high precision.  They have many practical use-cases, not only in offices and in the home, but also in retail to help merchandisers understand where people linger and what items they choose (or even put back).  And because it’s completely anonymous, it quells many of the privacy concerns that come with CCTV.

Back Office Productivity

Data is being used to drive efficiencies across processes like procure-to-pay and order-to-ship, areas that are the least visible to consumers, but have the most impact on the bottom line.  These efficiencies can happen in a diverse number of areas, from improving logistics in the supply chain to identifying fraud in invoicing.  The world’s largest retailer, Walmart, with 5,000 stores and 200 million invoices to process, has the sort of scale to drive more efficiencies with AI.

The Bottom Line

While still a maturing space, the democratization of big data and machine learning via cloud computing means that any retailer has the potential to weaponize their data to the benefit of their customers and their bottom line.

Read more insights from Digitas here.

Author: Tony Bailey, SVP of Technology, Digitas