When the first automated Amazon Go store hit the scene, small-to-medium and independent retail businesses thought the concept was only attainable for larger corporations with big budgets. While this was the case at the time, thanks to a number of technological advances over the past decade around artificial intelligence (AI) and machine learning, retail organizations of any size can now automate their sales floors without incurring unrealistic costs.
Because of the huge potential to reduce overheads associated with employees, improve sales efficiency, and gain valuable insights on product performance, it’s a matter of when, not if, widespread adoption of this AI technology, and these business models, in retail will occur.
So, while the concept of an unclerked, automated store may seem like it’s flown straight out of the pages of a Phillip K. Dick novel, the reality of these smart stores is the opposite of dystopian. Let’s take a look at why this is the case.
Familiar stores, just more efficient
Although the idea of an automated store invokes images of sleek, clinical and futuristic sales floors, stores with AI and machine learning capabilities will look much the same as they do now. This is because the aim of automated stores is to enhance existing retail performance by leveraging machine learning to gain insights around customer behavior, while also improving overall engagement. That said, there will be key differences for patrons — the most obvious being the absence of a cashier and register, as well as the associated lines as customers wait to check out.
The main difference between a standard store and an automated store can be found beneath the surface. Without AI infrastructure, store managers and owners are required to identify customer purchase habits via an analysis of customer demographics, brand availability, economic conditions, store marketing and sales data to maximize their profits. This is a costly and time-consuming process that also leaves room for human mistakes. Through the utilization of AI and machine learning, this function can be completed automatically — while mitigating the risk of human error — via AI-generated, data-driven insights delivered on a dynamic basis.
By utilizing these insights, store owners and managers can:
- Improve their supply chain and rely on accurate stock counts: This means that store owners can avoid over or understocking issues because stock counts are accurate, and replacement products can be ordered at the optimal time to mitigate shortages.
- Adjust pricing quickly: Machine learning capabilities identify periods of demand, as well as stock bottlenecks to adjust pricing and ensure maximum profits, as well as the sale of stock before it reaches its “best before” date.
- Optimize store layout: AI insights reveal customer purchase habits to place items in the optimal position to maximize sales, as well as the chance of impulse purchases.
- Improve customer experience: Chat bots, voice search, digital signage and other AI functions inform and direct customers to ensure they can find what they’re looking for without sales assistant intervention.
A retail experience customers can rely on
While data-driven insights can maximize profits and optimize inventory management procedures, the benefit of smart stores for customers is the other key selling point of this technology. The main value proposition here is an experience that customers can rely on every time they enter the store, with common pain-points like long lines, sold out items, and the requirement to interact with a cashier removed from the retail experience.
This preference for a reliable in-store experience is evidenced in the flagship project from retail juggernaut, Amazon, who in 2018 opened its flagship automated store, Amazon Go. In this Seattle-based store, customers could browse products, select their items and then pay with zero need to checkout or interact with any employees. Customers embraced this simpler way of shopping, too, with the project generating roughly $1.5 million per year in revenue. It has been so successful, in fact, that an additional 3,000 smart stores are planned for construction across the country, with a sales forecast of $4.5 billion by the end of 2021.
With this monumental figure in mind, it’s clear that there’s potential for a significant return on investment through the implementation of smart stores. Thankfully, the conversion from a traditional store format to an automated store is no longer out of reach for smaller retail companies. This is because of the emergence of providers who are able to retrofit stores of any size with the required technological infrastructure for automation. By doing so, they are able to offer a similar experience and the same benefits as larger retailers.
Although transitioning from a traditional store format to one where cashiers are no longer required may be an intimidating prospect for many smaller retail businesses, the benefits of making the switch far outweigh the risks. Through retrofitting stores with AI and machine learning infrastructure, businesses of any size can maximize their profits through the reduction of employee overheads and simplify internal processes such as stock analysis and management, all while enhancing customer experience. Considering these benefits, it’s just a matter of time until this contactless, automated shopping experience becomes the norm.
Credit: Google News