CX is king in commerce

Roberta Balcytyte at WPP’s Satalia explains how AI ensures that the customer experience (CX) is always king when it comes to commerce

Time-sensitive and rapid grocery, clothing and hot food delivery have widened our expectations of the shopping experience, and – thanks to retailers harnessing the power of AI – our expectations are increasingly being met.

“It’s all about meeting ever growing customers’ needs,” says Balcytyte. “Two consumer trends have emerged in the last, say, seven years. Firstly, customers want to choose when they want things delivered. The second, a newer trend, is all about satisfying the desire to have things delivered ‘now’ – or at least ‘soon’.”

The need for ‘when’

To satisfy this need as a retailer, you must truly understand what you can offer your customer. “You cannot just ‘hope’ to fulfil that need – you need to know whether you can deliver those items to the customer at what time and at what cost. These are not easy things to know at all,” says Balcytyte. This is what AI can tell you.

“Businesses have to employ the right technology which can predict – based on when the customer wants their deliveries, where they want them, the size of the deliveries, the vehicles available at specific locations – whether they can fulfil that need and at what cost. The retailer also needs to know how other orders are shaping that delivery network as well as the volume of traffic on local roads, the weather, future demand, and so on, before the retailer can offer potential delivery windows.”

She explains that, in the early days of delivery slots, many retailers were simply building their market share, not understanding all the parameters of a transaction. Now, the cost of meeting these heightened customer experiences is very much part of the equation and is why complex algorithms are at the centre of meeting customer expectations in a sustainable and cost-effective way for the business.

“A lot of retail businesses are now grappling with the question: how do we optimise our network to bring down the operational cost while still satisfying their craving for convenience? Retailers' planning systems must consider lots of different inputs and make a calculated choice within milliseconds about what to offer so that it makes sense from both the convenience point of view and the cost of meeting that need,” says Balcytyte.

“For example, the system must be able to predict that the costs will be high if the delivery driver must drive extra miles off the main route at a specific time when no other deliveries to that area are due, and the system must smartly suggest other more cost-effective time windows or be able to calculate the price of the wanted time window accordingly.”

The need for ‘now’

There has been a huge leap forward in ‘get it now’ deliveries. This is the space in which we have seen new entrants, and now big businesses are playing catch-up. But the operational costs of such an offer are huge and some entrants to the market have stumbled. Partly it is a question of scale, but also density – and information about impacts are necessary to optimise the system.

“The demand for this type of operation has already been created by well-funded start-ups. Customer expectation of very fast delivery is here to stay. Now the big players are scratching their heads and asking themselves how to keep up,” she says. “Let’s not forget that these larger players are well placed to give it a go and innovate because it’s practically an extension to their well-established and proven business models.”

Balcytyte says she is seeing clients going through a period of testing and learning. “This approach brings some operational complexity because, as a retailer, you have to adapt your placement of fulfilment hubs, extend the vehicle fleet with smaller cars or two-wheelers, and your picking and packing processes have to be able to scale quickly as you can no longer plan them in advance,” she says. The stakes are changing, and AI can help with that change.

“Technology helps us to predict demand, to make cost-effective dispatch decisions, and more accurately plan resource allocation and stocks. It also enables dynamic pricing which has been normalised by ride-sharing and food-delivery companies who offer ‘get it now’ services.”

She concedes that retailers have shown some resistance to dynamic pricing as it relies so heavily on algorithms rather than human intervention but, increasingly, there is an understanding that allowing algorithms to calculate pricing based on lots of different factors is likely to be part of the retailing mix going forward.

“It all feeds into how we build the technology, how we build confidence, how algorithms will develop – they can support the whole delivery system, not just same day but the whole system,” she says.

Crises call for efficiencies

There are so many crises to navigate at present, and optimisation of processes to manage cost and deliver the best CX despite adversity has to be at the top of any retailer’s wish list. “All these crises translate into higher costs for the consumer and the need for operational savings by the retailer,” says Balcytyte. But if a business is to continue to grow but still offer low prices as well as plan for a reduction in demand for non-essentials, it will need more than the human brain to figure all that out.

She says this is a space where AI technology through simulations can play a big role. “Simulations can help a retailer observe how market shocks impact a network and take actions based on predictions. It’s all about finding the best configuration of the network for dealing with either current or future disruptions,” she says. “And all the time, ensure the business delivers the best possible experience for the customer.”