Retail Technology

Automation has replaced the human effort of executing business processes. The latest report published by private sector think-tank McKinsey Global Institute (MGI) which assessed the effects of automation in various socioeconomic environments, suggests that 30% of the Earth will be automated by 2030.

With AI and VR systems taking over nearly all industry sectors in recent times, automation technologies have been instrumental in reforming commerce. Be it retail, apparel, healthcare, education or e-commerce, brands are moving towards acquiring these futuristic technologies. This implies a greater displacement of human resources and a continuous shift towards automated processes in business. And, at the core of a significant part automated processes within consumer retail, lies access to accurate, structured and digitally available product data.

When we talk about automation, it includes everything from m-commerce applications to robots in workspaces. Automated technologies like virtual trial rooms, digital shelves, self-stocking robots, self-checkout kiosks, drone deliveries, have all contributed towards ushering the next wave of commerce.

Customer services and automated software solutions have enhanced the manner in which brands are engaging with users. However, new technologies come with a complex set of requirements and it is not possible to navigate these technologies unless there exists a source of product data to complement them.

It is also safe to say that product data form the driving force behind many automated consumer retail processes.

Whether you talk about digital shelves, scan and go mobile applications or AI Chat Bots, product content serves as a common thread that these applications would need to access in order to do what they do.

For instance, let us take the example of digital shelving. Rather than manually update printed shelf labels, prices and other product information every morning the store opens and through the day, digital shelves can be centrally updated via a system and reflect information changes in real time. However, they need to be connected to a source of product data and attributes in order to function.

Image Source: The Verge

Walmart’s digital shelves are also gaining more attention but not just for the way they display information but the way they work with robots. The self-stocking, aisle roaming robots move around the store scanning shelves monitoring stock levels as they go and identify spaces which need to be replenished. These robots take on tedious tasks such as restocking shelves and identifying which products are labelled incorrectly. Such integration of automation into the workforce has replaced the human effort of performing tasks that are repetitive and predictable. As a result, employees can focus on bigger challenges while the basic tasks are being automated. Again, in order to identify products, reorder them, identify package size, quantity, units on shelf and more, these systems need access to a live product data source.

Even if we talk about automated in-store sales and demonstrations, such as in-store demonstration videos and interactive kiosks which are not just limited to digital shelves, they require data. And this data needs to be structured and centralized. Scan and Go applications, much like Amazon’s prodigy app, demand structured product content to support its automated processes like self-checkout, billing, digital invoices and payments.

White the self-stocking robots, automated call centres, self-checkout kiosks and mobile ordering systems do their work, it’s up to employees to focus on supplying these automated systems with the data they require in the right format.

As talks and efforts around automation in the retail industry grows, organisations need to emphasise on building a centralized Product Data Hub to power these automated applications setting strong foundations for the automation they deploy.


June 2024