Category: AI

Paid partnership with Manhattan Associates

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Last week, I travelled to the beautiful city of Barcelona to attend Manhattan Exchange. This is Manhattan Associates’ annual European conference and always a great opportunity to hear directly from some of the region’s biggest retailers and brands. So what stood out for me this year?

There were a few distinct themes that permeated throughout the event – unification of physical and digital commerce, store employee empowerment, and the need for both retailers and technology companies to continue to “shatter the status quo”, in CEO Eddie Capel’s words.

But what really sparked my interest was learning more about generative AI’s impact on customer service. Real-time responsiveness is very much a trend to watch for 2025. Here are my top takeaways:

• Retailers are increasingly comfortable experimenting with gen AI but most of the use cases that we talk about today are centred on e-commerce operations – writing marketing copy, coding, creating images, etc. So, it was interesting to hear how European retailers are now encouraging staff to use gen AI in-store. Using voice, rather than text, this enables store associates to quickly identify solutions and better serve the customer. Expect a whole lot more of this in the coming months.

• There was a clear consensus that AI chatbots in their current form (ie. not the gen AI kind) are an abominable experience for the customer. They often spit out generic or irrelevant information, or redirect the user elsewhere, all of which lead to customer frustration and potentially lasting brand damage.

• Gen AI chatbots, meanwhile, are going to be a gamechanger. This next iteration of the chatbot, like Manhattan Active Maven, can resolve more complex issues. For example, instead of just asking “Where’s my order?”, customers can ask things like: “What size was that polo shirt I ordered last year?” or “Remind me how much tax I paid on that purchase.”

• One of the top reasons customers get in touch with a contact centre is because they forgot to add a discount code at the checkout. This can be quickly resolved by a gen AI chatbot. Similarly, if a customer changes their mind after making a purchase – for example, they want to modify or cancel the order or alter their fulfilment method – this is another easy task for gen AI that benefits the retailer, customer, and planet.  

• Traditional chatbots can handle between 20-30% of inbound customer queries without any human intervention. With gen AI chatbots, this rises to more than 50%, freeing up staff time to focus on more valuable tasks like upselling or dealing with more complex customer issues.

• Gen AI chatbots will drive efficiencies and improve the customer experience, but they won’t replace humans. For example, gen AI will draft an email for a contact centre employee to send to the customer following an interaction, but the employee can tweak this and must sign it off before sending. Similarly, the tool will generate post-interaction notes, saving employees another 45-50 seconds each time. 


• However, sometimes no AI is needed at all, and customers just want a human – albeit one that is still very much tech-enabled. We heard how a major European retailer allocates a QR code to each store employee, allowing shoppers to scan the code and continue the conversation with that member of staff after leaving the store. Now, as Green Retail World editor Ben Sillitoe pointed out on my podcast recently, we might not be rushing to scan the QR code of staff at our supermarket checkout, but for those more considered, bigger-ticket discretionary purchases (think fashion, beauty, luxury, home, electronics) this is exactly the kind of innovation retailers should be pursuing.

For more on Manhattan Associates, visit www.manh.com