Five Ways AI Will Disrupt the Retail Workplace

Ally Feiam By Ally Feiam | 21 Nov 2019

Artificial Intelligence (AI) is transforming every industry, and is already making significant inroads in the retail space − both online and offline. According to a Capgemini global survey of 400 retail executives, AI could save as much as half a trillion dollars annually by 2022.

Even if that estimate is wrong by an order of magnitude, there’s no doubt AI will make a huge impact. Here are five ways AI is changing the face of retail:

1. Visual Search

For years, the most common way to search was with text (or, more recently, voice, which is also based on words). The next big thing in search is visual search, where AI recognises objects in an image. This is a natural way to search with mobile devices: See something you like, take a photo, share it with an online store, and AI recognises it and finds it in the catalogue. Not surprisingly, it’s most in-demand with young shoppers: ViSenze, an AI company leading the way in this technology, found 62 per cent of Gen Ys want visual search.

2. Advanced Recommendations

Amazon’s recommendation service pioneered the technology behind automated cross-selling and continues to lead the way. As AI has matured, recommendation services have improved, and often make better recommendations than humans.

With more than 70 per cent of younger (Gen Y and Gen Z) consumers indicating they are likely to buy products based on a recommendation, It’s not surprising that retailers are investing in recommendation engines. If you don’t want to build your own, Amazon has made their technology available to others through its Amazon Personalize service. This is no longer exclusively an online service, either. “Beacon” devices in retail stores can transmit information − such as deals, special offers, and recommendations based on buying history − to smartphones as shoppers enter the store, walk around, and linger at specific displays.

3. Hyper-Personalisation

Recommendations are just one of the ways retailers provide personalisation to their customers (called “hyper-personalisation” to emphasise it’s focussed on each customer individually). Customers value that personal touch: Deloitte research suggests over half of them like personalised products and services, and one in four will pay more for them.

In the online world, it’s easy to reorganise digital bits to personalise every step of the buying experience. For example, UK retailer ASOS provides a “Fit Assistant” to find clothes that fit different body sizes, and skincare brand Olay offers a “Skin Advisor” to create a personalised skincare regime.

AI − with facial recognition technology and past behaviour analysis − can also help in-store, advising staff on how to deal with each customer individually. Personalisation is not without risks, so retailers must approach it with care. In 2012, travel site Orbitz came under fire for showing higher prices to Mac users (assuming they could afford to pay more). As AI becomes more sophisticated, it will make more of these decisions, sometimes in ways humans can’t predict beforehand or explain afterwards.

4. Predictive Analytics

AI’s ability to manage large volumes of data means it can now predict an individual customer’s behaviour based on the behaviour of other customers. This “predictive analytics” is another kind of hyper-personalisation, but this time based on other people’s behaviour.

As one example, French retailer Showroomprivé.com tackled the issues of reducing customer churn and increasing customer loyalty by using AI to analyse the browsing behaviour of its two million daily visitors. The AI systems found patterns of behaviour that indicated a high potential of not buying, and then customised the online experience to encourage those customers to stay and buy.

5. Security Alerts

As customers demanded less friction in the buying experience, retailers loosened their security requirements, calculating that the increased sales would compensate for the inevitable shrinkage. However, AI is now helping to reduce the losses. Some of the features already described above − such as beacons and facial recognition technology − can also increase security. And even for businesses with traditional video surveillance cameras, AI surveillance can help to detect suspicious behaviour.

Technology analyst Gartner predicts AI-derived business value will exceed $5 trillion by 2022. Most smart retailers expect AI to play an increasingly important role in their business. If you’re not already using AI, it’s not too late – but don’t wait too long!

Gihan Perera is a business futurist, speaker, and author who works with business leaders to help them lead and succeed in an uncertain but exciting future.

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