Machine learning in retail can help to examine customer patterns of consumption, but also can help to manage stock and ease the workload on members of staff. Retail is a front-facing industry by design, so the average consumer is already seeing the future of AI in retail taking place in their everyday life. AI and retail mightn’t seem to be the perfect fit at first glance – so much of retail is associated with interpersonal interaction – but it goes deeper than that.
Take for example a particularly important function of AI in fashion retail, as well as AI in retail generally; inventory management. Machine learning in retail can help to forecast demand, supply and plan around those factors. It will ultimately almost eliminate cash-in-stock and out-of-stock scenarios for companies who implement the technology and utilise it in the correct way. A computer will almost always provide better results than more traditional methods when it comes to inventory management.
Quality assurance and predictive pricing are both also vital aspects of this industry, and machine learning in retail can create another game changer in that process. Computers can generate an expected cost list for raw materials taking into account supply and demand, inflation and market trends to create a general estimate which can be used for planning very far into the future. For quality assurance, the AI in retail can cast a discerning eye on what is being produced by the manufacturer. There will be assembly lines of work based on a predetermined set of parameters, and the computer will whizz through it at a speed that manual workers can’t and shouldn’t compete with. If an end product doesn’t appear to be up to scratch, the AI in the retail system will flag it with a member of the team who can do a quick manual check, as opposed to the expense of having people do that check on every product. This can shave a lot of unnecessary expenses from a business’s bottom line.
Data can help retail businesses to connect with their customers – as dystopian as that sounds. When stock and quality assurance are being taken care of by computers, the front-facing staff have a better likelihood of having time to engage more with customers. This will ultimately lead to fantastic consumer relations and inevitably bigger numbers coming in for the bottom line. It doesn’t matter if your company is a small family owned business or a franchise of a big multinational – customers remember their experience, and that will reflect in your footfall. You’re already beginning to see the implementation of self-scanners for grocery shops, and now even Amazon-owned stores worldwide where customers don’t even need to pay – it’s done automatically when they put items in their cart. Things like this will soon become the norm, and the data can be used in even more interesting ways.
Demand forecasting is something we touched on earlier, but it is a game changer for businesses. Analysing sales numbers, AI in retail will utilise machine learning in retail that has happened and advise to owners which products they should have more of, and with which ones they shouldn’t bother filling the shelves.
We haven’t even discussed online retail yet. AI in retail has already taken a massive grip on online retail. During the covid-19 pandemic, we have seen exponential growth in that department, and machine learning in retail has been developing as quickly as the business itself. The ‘cloud’ allows for AI in retail to handleworkloads that require volumes of data from many different sources to be stored and processed. Demand forecasting machine learning and online product recommendations are just one part of this sort of thing. It is most obvious in online shopping when google cookies maintain your data, and after seeing that you are in the market for a product, will cater ads to that interest that you have.
There will always be a market for the traditional methods of retail, with cashiers greeting customers and serving them. But we are already beginning to see the results of machine learning in retail and AI in retail as a result. There are whole stores with no front-facing staff at all, and an abundance of self-service options at checkouts in any mainstream grocery store you visit. This is going to be the norm as this AI in retail technology continues to expand, and we garner a better understanding of consumer patterns. If customers prefer dealing with human beings, then it is highly unlikely that the business model will change to that of the experimental Amazon Go shops that have popped up in the United States of late.