How machine learning is changing the face of retail

Dunhumby-machine-retail According to dunnhumby, global leaders in customer science, machine learning will bring about changes of a similar scale or greater to that seen in the industrial revolution of the nineteenth century. But what effect will this have on our shopping experience?

Machine learning is a type of artificial intelligence, powered by large-scale data that provides computers with the ability to learn without being explicitly programmed. It’s already having an impact on diverse aspects of everyday human life, including the retail industry. 

The information can also get better over time– the more data and feedback they get. The impact of this technology is that it provides a massively scalable, never tiring, consistent quality digital workforce that can perform tasks we previously thought could only be done by humans.

Machine learning is helping our lives become more enabled, streamlined, and friction-free. Learning techniques have been known about for three or four decades, but it’s only with the dual advances of fast parallel computing and massive data sets that machine learning has proven its worth.

How is machine learning changing the face of retail?

MD of dunnhumby SA, Graeme Tulloch comments, ‘Through new data science techniques and vast increases in available data, dunnhumby is using machine learning to assist retailers in predicting the future. It stimulates scenarios that forecast outcomes and pinpoint critical action areas within an enormous amount of possibilities.

‘Most retailers are already forecasting to some extent. When a product goes on promotion, they have an idea of the amount of extra product they might expect to sell, and measuring the accuracy of these forecasts is relatively straightforward. With machine learning (specifically neural networks) we can analyse sources of data not in a structured form – such as customer comments or video data. Historically these were difficult to analyse beyond the anecdotal. The latest techniques have opened up a new world that allows retailers to explore data which previously may have been discarded.’

Retailers (like every other sector of business) have never had more data and yet in the future, they will never have so little data. A wealth of dunhumbydata about products, prices, sales performance, costs, availability, logistical activities and consumer behaviour is now available. The combination of stores’ delivery channels, products, and time-consuming product attributes, creates a vast field of metrics to keep in check.

Every form of data can be analysed for every category, multiplying an already vast amount. With so many data points it’s a seemingly impossible task for even the most experienced retailer to be able to identify key under- and over-performing areas. The use of machine learning in new retail tools enables this vast field to be examined. Being able to identify, understand and act upon the key contributing factors will revolutionise the ability of companies to drive their business performance.

Some things are far more complex to predict. Economic, social, legislative and technology changes can have dramatic impacts on customers’ behaviour. The impact of a tax on added sugar in products may well reduce demand due to the change in price, but there are other unforeseen changes. This could include changes in the acceptance of giving children sugary drinks or the willingness of retailers to stock certain items in certain locations. Tools such as agent-based modelling and reinforcement learning will allow companies to investigate the consequences of their own actions coupled with external forces.

When it comes to the scale of impact machine learning will have on the retail industry, this is just the tip of the iceberg. The revolution is here for retailers willing to take the next step with data science.