Artificial Intelligence for Real-Time Retail


Artificial Intelligence (AI) has become a well-discussed term in recent years, finally moving from sci fi pipe dream to real-deal opportunity for businesses to improve efficiency and service. As everyday shoppers, we experience the effect of AI as recipients of personalized advertising and product recommendations. That’s not all it can do, though, as AI is becoming a powerful tool for in-store retailers to turn imprecise and inefficient backend processes into value-drivers.

But why do we need AI for this? It’s not like retailers have been starved for data analysis or don’t know how to run their businesses based on decades of experience and customer relationship building. And yes, technology has been improving nearly every aspect of retail for years. But even when retailers adapted advanced rules-based algorithms to ease the burden, their improvements were capped by the limited power of historical data to tell the full story – which it really never does. Let’s explore two ways that AI can impact customer engagement processes in ways no other technology quite can.

For More on Technologies of the Future

The Innovation Lab at NRF 2019 will showcase top "technologies of the future" helping retailers deliver seamless customer convenience and thoughtful experiences. Visitors will experience the most recent advances in artificial intelligence, augmented reality, machine learning, facial recognition, big data, robotics, and more. The Innovation Lab will take an in-depth look at how these technologies, deployed across the shopping journey, are driving increased conversion and cost-saving efficiencies.

For more on NRF's yearly expo, check out the RIS editors guide "Next Stop: the NRF Big Show" and get a short glimpse into the speakers and sessions that will define The Big Show 2019.

Digital Signage

For well over a decade, retailers have relied on digital signage in stores to promote dynamic messages, ranging from store alerts to promotions. In some cases, it’s not only a driver for sales, but also a space that can be sold to CPG manufacturers as a branded display at the point of decision.

Yet, many retailers have failed to succeed in using these signs because they weren’t ready to hire people to keep the program effective – it takes a lot of work to create and update the content. It’s also really challenging to dictate behavior with a message or change mass buying behavior this way unless there’s a great discount available. Compound these issues with a fundamental lack of dynamic, scalable infrastructure, and it was simply too hard to create a real-time, mobile-ready promotional presence.

But now with AI, retailers can predict product sales far into the future and automatically push a unique message to the digital sign based on how real-time activity compares to expectations. For example, ice cream is generally expected to sell less well in winter, but a sudden heat wave might have shoppers clamoring for the freezer aisle. The AI system would automatically identify sales as higher than expected given all factors at play, triggering an alert to the digital sign, which in turn loads a graphic that tells shoppers that ice cream is selling particularly well today. Shoppers, recognizing the merit of their peers’ decision, follow suit.

Not only does this increase sales, but also improves in-store and long-term customer satisfaction. On the retailer’s end, there is no need to spend time setting up or managing a certain promotion. The automated system instead succeeds just by reinforcing subconscious whims. The important thing is that with a digital screen supported by AI, you don’t need to know why a trend exists. You just need to know it does exist in order to capitalize effectively.


Another unique content-adaptive feature of AI is the ability to deliver far more impactful, dynamic and personalized newsletters. First, AI allows retailers to distribute personalized newsletters that contain content that meets their expectations and preferences. But the benefit most retailers aren’t yet using comes once customers start opening the content.

When people start clicking, the content hits the AI engine, which can analyze and update their responses to the content in real-time, based on what they click on and spend time reading. Then, for future readers, the AI can instantly remove or reduce the prevalence of underperforming content, raise the profile of high-performing messages and improve both customer experience and ROI.

This ability to react to not only respond to expected outcomes but to the actual results as they unfold is a major departure from what retailers currently can do. Setting goals and responding once results come in days or weeks later will become a relic of an archaic system.

Automated, Real-Time Relevance

While those who ignore history are doomed to repeat its failures, only those who can make intelligent predictions about the future and adjust to real-time environments on the fly will thrive in coming years. AI stands to change the game, but it also requires a scalable and flexible architecture that can seamlessly move data across applications to create optimal outcomes across the organization. Only then can stores realize the true power of AI in the enterprise.

-Michael Jaszcyzk, CEO, GK Software USA

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