There are two kinds of people in the world: those who love shopping and those who would rather watch paint dry than step foot into a mall. I fall into the latter group. For me, shopping is a mission.
The process usually goes like this:
No, thank you.
I would much rather shop online, even though it has its own drawbacks: I can’t try on anything I buy and I might have to wait a day or two to receive my order, which is not ideal in an age of instant gratification.
But I might still be converted.
New and emerging technologies such as artificial intelligence (AI), machine learning and cognitive computing – underpinned by big data and advanced data analytics – could completely transform the shopping experience as we know it. While still in its infancy in South Africa, a handful of retailers are testing some pretty cool technologies in an attempt to improve the shopping experience and better serve their customers.
Research by World Wide Worx found that online shopping in South Africa is expected to reach just 1% of overall retail spend in 2016, constrained by challenges such as high data costs, a lack of trust in e-commerce and a large unbanked population who do not have the means to transact online.
The adage that online is killing the brick-and-mortar store might be true for more developed markets but, for now, South Africans still flock to the more than 2,000 shopping malls across the country, limiting their online activities to window shopping and price comparison.
If this trend continues, then South Africans could be in for a real treat when these new technologies make it to our shores.
Imagine the store of the future: facial recognition technology detects when you walk through the doors. The retailer already has an idea of the type of clothing you like based on past purchases and the parameters you’ve provided them with, like your height, weight, etc. You stand in front of a mirror and AI technology immediately “dresses” you in an outfit based on your preferences and unique style. You easily flip through colours and styles without once seeing the inside of a dressing room. You make your decision and a robot brings you your purchase. You thank him or her or it and walk out the store – no standing in queues to pay. In fact, the physical act of paying is completely redundant. The retailer already has your card details and your account has been debited for the purchase. It’s instant gratification on a whole new level.
The Amazon Go concept is a perfect example of this.
The idea behind these smart stores is to replace certain tasks that humans perform today – like stocking shelves, ringing up purchases, etc, with real bots, chat bots and other artificial intelligence. While there is still a long way to go before this becomes reality, bots will be able to understand what we’re asking them, process that information instantly and move us along the purchasing journey quickly, efficiently and with a greater degree of accuracy and customer satisfaction.
The ultimate goal is to replicate human thought processes but instead of telling the machine what it is doing right and wrong – like we do today – the machine will continually and automatically learn from new data and inputs without any guidance from humans. We’re still in the trial-and-error phase. Sometimes we get it right, sometimes not, but humans are still playing a large role in AI applications and we’re not ready to hand over full control to the bots just yet.
The idea that we could all one day have our own personal shopping assistants and stylists probably excites a lot of us. But how does the retailer benefit from investments in these new technologies?
Waste, inefficient supply chains, poor stock management and products that are priced out of the market are just some of the reasons retailers could be haemorrhaging cash and losing customers.
AI, cognitive computing and machine learning could completely change the game for retailers. When machines learn about demographics, weather patterns, buying trends and GDP growth for a particular area, they can tell a retailer which products to stock and how to price them for maximum sales.
Machines will know that summer clothes will move off the shelves in areas where it starts to get warmer sooner and that the retailer can reduce the price of its winter clothes in that store. However, it might still be chilly in another province, meaning it’s a good idea for the retailer to keep its winter clothing prices unchanged for maximum revenue.
Machines will know that people living in area X are prepared to spend more on a loaf of bread than those living in area Z. They will know to stock bigger sizes of certain items in one area because demographics show that the population is generally larger there.
Of course, humans can do all of this but it’s labour intensive and we don’t always get it right. But if retailers are prepared to hand the reins over to the machines, never again will they run out of stock, have too much stock, have the wrong stock for a particular area or sit with incorrectly priced stock. This will allow them to completely optimise their supply chains so that they get the best prices from their suppliers based on real demand, not guesswork.
In essence, demand planning and optimisation allows retailers to have the right mix of products, for the right customers, at the right store, at the right price, at the right time.
While some retailers in developed markets are already benefitting from AI, machine learning and cognitive computing, South Africa still has a long way to go. The biggest challenges to implementing these technologies locally are skills shortages, poor data quality, challenges with analytical modelling and the fact that analytics has not yet been fully automated and is still a manual process. South African organisations are still coming to terms with basic analytics, although some retailers are applying AI to certain segments of the customer experience and are seeing impressive results.
It’s going to be a journey of trial and error. As with most new technologies, there will be tinkerers and early adopters, there will be massive failures, and there will be those who will take a wait-and-see approach. But, as with cloud computing and other ubiquitous technologies of today, eventually AI will become commonplace and those who do not embrace them will be at a distinct disadvantage.
Those organisations that will rise above the rest are the ones that reward innovation and that support the tinkerers from the executive level. They understand that risk and failure are part of the journey but that they are also part of the learning process, if we are to get it right.
And when we do get it right, retailers will realise massive cost savings, which they can pass on to their customers and combine those savings with personalised recommendations to create the ultimate shopping experience.
I, for one, cannot wait.