3 ways AI integrations are shaping the future of retail

Companies that provide a more compelling retail experience enjoy up to 7 per cent higher sales revenues than average, and up to a 10 per cent greater shareholder return too. In a retail market that gets more competitive by the day, that’s an advantage well worth having.

But in a market that’s more volatile by the day, and faced with consumers whose expectations have never been higher, delivering an outstanding retail experience can be extremely challenging. Somehow, retailers need to find ways of staying ahead of trends that can change far faster than their ability to launch new campaigns or source new stock.

One of the best ways to do this is by using artificial intelligence (AI). AI can help retailers predict customer needs, enabling them to respond to changing demand before it happens. It’s also able to support companies in managing scarce resources, such as stock or staff time, and can even help them build deeper relationships with customers by conversing with them.

So, as we head into another intense festive season for retailers, now is the time to get serious about using AI to get ahead of customer needs, help resources go further, and deliver a customer experience that both surprises and delights.

Here are three ways to make AI work for you…

1. Improve the customer journey

   
   One of the most frustrating aspects of being a marketer is to run a series of great customer acquisition campaigns, only to see all the leads that you generate trickle away through leaks in the sales pipeline. AI can help fix this problem by analysing where in the customer journey those leaks are occurring.
   
   For example, it may be that despite having a lot of traffic to your online store and/or footfall at your retail outlet, customers keep bailing out. Using AI, you can work out whether that’s because they can’t find what they want, because the checkout experience is confusing, or because they can’t use their preferred payment method. And once you know the exit points, you can act to address them.
   AI can even help with that too–as we recently saw with the fashion brand Zara when it opened a new flagship store in Madrid. The store integrates many automated features, all designed to improve and accelerate the customer journey. These include scan-and-go mobile payment, with no need to queue at the checkout, and automated return points. Crucially, these features are connected to an AI-driven backend, which analyses people’s interactions with them, allowing the store to constantly improve the customer experience.
   Then there’s Selective Marketplace, which owns the womenswear brands Wrap London and Poetry. The company used AI-driven solutions to seamlessly route calls to the right teams and agents, helping to minimise delays and queuing. The system also instantly delivered insights and customer information to the contact centre teams. Customer approval ratings rose to 97 per cent as a result.

2. Enhance demand prediction to boost efficiency

   
   Another way AI can help you stay ahead of a changing market is by improving demand prediction. Even at the best of times, demand forecasting is difficult to do well—particularly for new products, without a bank of historical data. As we head into a recession, correctly predicting the impact of multiple variables—including inflation, unemployment trends, pay settlements and consumer sentiment—on each other and on consumer demand becomes even more challenging.
   AI, with its ability to process data faster than humans and spot correlations and trends even in the largest and most complex datasets helps to solve this problem. Using your own data and, where relevant, external datasets, AI can identify patterns in customer buying behaviour. This means you can precisely tailor stock purchasing, staffing levels, and other key decisions to match peaks, troughs, and fluctuations in demand.
   According to a recent study by McKinsey, using AI-driven forecasting can significantly improve supply-chain management—something that confers a potentially massive competitive edge, particularly with the current supply-chain crisis—reducing errors by up to 50 per cent. The same survey also found it can help reduce warehousing costs by up to 10 per cent and admin costs by as much as 40 per cent. In some sectors, AI can even automate as much as 50 per cent of all workforce-management tasks, reducing costs by anything up to 15 per cent.
   What’s more, using AI-driven forecasting means less waste, lower storage costs, and better asset-utilisation–all of which leads to improved return on investment (ROI) and more efficient staffing. This, in turn, results in increased cost efficiency, which is a huge benefit in today’s hyper-competitive marketplace.

3. Deliver better customer service

   
   You can also apply AI directly to customer service, most obviously through automated chatbots. Here, you program your customer experience platform to activate an automated chatbot if it notices a customer’s journey has stalled, indicating an imminent bounce.
   Tellingly, 65 per cent of customers say they now prefer to shop with retailers that offer this kind of hassle-free, automated experience. And the technology to deliver this experience is improving all the time.
   
   By plugging your customer experience (CX) platform into your customer relationship management (CRM) systems, you can also prioritise communications from customers who are big revenue drivers, routing them to the right service team as quickly as possible. With Zendesk Intelligent Triage, for instance, AI scans the contents of a ticket to understand the customer’s needs, then automatically routes that ticket to the team best able to resolve it, accelerating resolution and improving the customer experience.
   In addition, AI platforms can automatically guide customer service agents to the best solution for each customer query. This helps to resolve the query faster and improve the overall experience for customers. For instance, once a ticket arrives with the agent, Zendesk Smart Assist uses the text analysis performed by Intelligent Triage to provide the agent with the three solutions most likely to resolve the issue.