Remember the era of the shopkeeper? You would enter a store during fixed open hours, and a bell over the door would ring as you crossed the threshold. The proprietor would greet you and probably knew what products and brands were of the most interest to you.

Modern retail is trying to deliver the same experience at a larger scale in a far more complex world. There are dozens of different doorways through online stores, electronic marketplaces, phones, social media and physical storefronts.

Globalisation, mobile technology, powerful search tools and ubiquitous connectivity mean the local store has been replaced by a massive marketplace that can be accessed from almost anywhere, whenever the customer wants, from numerous entry points.

It turns out that while old-world shopkeepers might have thought their products were critical, their knowledge of the customers and what the customers most liked or wanted was their key asset. And that does have a natural role in the world of digital commerce.

Know your customer 

Cognitive computing — the use of algorithms to detect “signals” in data — allows retailers to understand how their customers move through the entire product journey. But it’s more than simply looking at data and trends. Cognitive computing uses behavioural analytics, as well as machine learning and artificial intelligence (AI), to do what those shopkeepers did: understand the customer.

Chanel Costabir, founder of The Lingerie Boutique in Melbourne, Australia, says both her deep knowledge of details and her ability to step away and look at the big picture let her better understand the ordering patterns of cohorts of customers and individuals. The use of data allows her to understand the behaviour of even first-time buyers, who typically make one small purchase and then, assuming they are happy, follow up with much larger purchases a few weeks later.

The climb toward a more digitised and intelligent retail system may seem insurmountable for many retailers. Creating specific areas of focus can help funnel limited resources into areas where the return on investment can be maximised. For simplicity, a retailer should focus on three core areas: logistics/warehousing, delivery operations and the customer life cycle.

These areas are critical to retail success and are also likely to either already be data-rich or have the capacity for relatively easy data collection.

Find the benefits

By injecting AI, demand planning can be built around more informed decisions when maximising inventory efficiency. Unlike the old shopkeeper who relied on gut feelings, it’s possible to automate ordering through an understanding of what’s been sold before, an analysis of trends, and interoperability with suppliers that are leveraging stock and holding only optimal levels of inventory.

There is a difference here, compared with how the old-world shopkeeper worked. In the past, the focus was on making sure the store had enough stock, without overburdening the proprietor, to ensure that cash flow was positive.

In this new model, the focus isn’t on understanding retail operations but on ensuring that the customer is at the centre of everything.

This goes from having multiple points of ingress to the store — a combination of different digital shop fronts as well as, in many cases, a physical presence — through to making products available based on the needs of specific customers rather than guessing what the market might want.

Embark on the journey

The journey towards intelligent automation starts by recognising the opportunities it brings and accepting the need to develop the right business model.

Organisational change management is critical. For example, Amazon is shifting from being a purely online retailer to embracing bricks-and-mortar stores. It isn’t throwing away everything it knows about online retail but is instead leveraging its experience when it establishes the Amazon Go stores.

Amazon is creating a new doorway for customers who prefer a visit to a physical store over an online experience. And while it is a big step, rather than trying to boil the ocean and take over multiple bricks and mortar stores, Amazon started with one store and used the knowledge before expanding.

One mistake made by many retailers is to think that they have to apply new technologies to everything in one fell swoop. However, it is possible to embark on a relatively simple adoption of a commodity AI solution that’s available and can be tailored easily. Then, it can be scaled and adapted to broader needs.

Start slowly and have a plan for growth as you learn.

Avoid the pitfalls

Retail innovation demands a shift in how operations are managed. Getting people, processes, technology and culture into line is critical.

Many retailers also neglect to pay sufficient attention to payment gateways. While we talk about going digital on supply chain and customer platforms, point-of-sale transactions often miss the AI investment they merit. Many customers have positive experiences when searching for products only to abandon shopping carts because the payments process to close the transaction is too complex or difficult.

And cybersecurity is now a major concern as well. Bolting on security at the end of a project seldom delivers a robust and effective solution that is compliant with emerging laws and protects customers and their data. Security needs to be considered at the start of a project and embedded into the design of new processes and systems.

The benefits of embracing new retail technologies are myriad. But they start by taking a customer-centric view and then building processes around them. By understanding the customer, businesses can offer better services that are delivered with greater efficiency and effectiveness.