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Jason Goldberg, SVP Commerce & Content Practice, SapientRazorfisI came to retail at a time when the retail landscape was dramatically changing. At the time, computer city superstore was the first big box concept for technology. But the interesting part was that the retailers only sold B2B technology in a self-service environment during the first time when consumers were starting to shop for technology. The whole concept of these big box stores with huge assortment was the first in integrating a lot of professional services and interesting amenities within the retail environment. Moreover, the interesting part was that retailers could no longer follow the rules of their predecessor; they had to create new ones. They now had to invent what would work, listen to the customers, and adapt to the practices of the task in new ways to meet unique demands. During this time, customers’ expectation has just been changing in quick succession.
"AI does a better job of assorting and predicting demand from customers as well as matching supplies to demands"
Now everything involves experimentation and there have been a bunch of new experiences, capabilities, and practices that have been tried, some of which were very successful. Nevertheless, the customers are clearly insured and we have these skills to listen to what they want, what they expect, and just do our best to meet that expectation. Therefore, it has been a paradigm shift from a retail-centered view to a customer-centered view.
The advancements in the cloud and the data access capabilities have been, for the first time, able to deliver some of the customer-centric promises that technology has been making for the last 10-15 years. On that note, 100 years back retail was very personalized, the sales associate knew every shopper, their preferences, and each customer got a very personalized experience. If those customers change their buying behavior then their sales person would know this, consequently, the customers got a very one-on-one experience. As the world and the population exploded, everyone was forced into this want of many experiences and retailers treated each consumer in the same light. But for the last 15 years, the retail technology promises have always been that technologies are going to enable us to go back to one-on-one experience with each customer on a much broader scale. We can see the potential in retail technology but until very recently struggled to deliver, we can talk about CRM but CRM was not available at the point of decisions where shoppers were interfacing with the sales associates on the floor of the store. It was maybe good for post-purchase emails but was not really good for helping customers make some purchase decisions on the sales floor. Today e-commerce has interesting capabilities around product recommendations and better product merchandising but none of that experience is available in the store with a majority of the purchase decisions. The ubiquitousness of the cloud and the data from the systems of separate silos are being aggregated and shared across all the touch points.
Artificial Intelligence (AI) and particularly, deep machine learning, are the disruptive retail technologies. Retailers have struggled to act on the abundance of data created and leverage all that data for each customer. This problem has fundamentally been solved by machines learning.
For the last hundred years merchandising has been a magic human skill and retailers hired people that have high prediction skills so as to predict what customers would want; but now the most successful retailers are actually replacing human beings with AI. Moreover, AI does a better job of assorting and predicting demand from customers as well as matching supplies to demands. This is a huge disruption for many retailers hold the human merchandising in high regards and it’s a very difficult transition to rely on technology to make the decisions. Retailers have been talking about data for a long time but are now able to unlock and aggregate the data into the cloud to enable all kinds of new experiences. Hence there has been an evolution of overwhelming majority of retail management systems based on on-premise and point solutions.
Retail management is on the verge of becoming more useful due to AI and big data. Hence, the stores delivering them will dramatically change the retail landscape. When we look at the most successful concept in brick and mortar retail, they involve human interaction with customers. Retail is witnessing differentiated shopping experiences as a result of employees’ interaction and it is going to be really interesting when the employees are provided with real-time technology and AI. Imagine employees wearing a headset with AI and are listening to the conversation that the sales assistant is having with the shopper. The AI analyzes the conversation and provides the sales associate certain information to help them make product suggestions based on expert recommendation systems. Meanwhile, the AI also checks inventory in real time and it is learning from other conversation that other sales personnel have had in the enterprise and creates the most useful suggestion and answers to each question. I believe it is very likely that every sales associate is going to have AI voice assistant in future to help them deliver the best possible customer experience.
It is important to remember that all of this technology is in the service of giving the customers better experiences. Sometimes as technologist we want to implement this new technology because it seems new, better, besides we get tired of the old technology and that is a perfectly understandable human emotion. The technology standard should be based on the display of how precious our resources are and the things that are going to improve the shopping experience for the customer.
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