AI in Fashion Merchandising: Bringing the Fun Back to Retail Teams

All the fun has been sucked out of fashion retail merchandising in recent years, believes Paul Sprackling. But he hopes that with the adoption of new technology some of that enjoyment will return.

Sprackling is a senior merchandising leader with a long track-record in some of the UK’s most beloved brands.

“I feel merchandising was a real fun thing to be in a number of years ago,” he says. “I feel people have lost that because there’s so much data to crunch, there’s so much reporting to do. What AI can give you, or what a new system can give you, is some of that time back to do the parts of the role that can turn it into such a great thing.”

Why fashion merchandising has lost its fun and how AI can helps

As Sprackling points out, most merchandisers are working with interesting products, but too often it becomes just numbers on a spreadsheet. He is adamant that they should get out of the office and into the stores to see the clothes on the shopfloor and understand how their customer interacts with them.

Of course, he realises that not all systems are the panacea they are made out to be. In a recent interview with Nextail, he set out the various aspects of new technology introduction that any retail business, and especially its merchandising department, ought to consider as they select and implement any system.

He highlights the need for good, robust data; the importance of a vendor who works collaboratively; and the need to ensure your team feels involved and appreciated.

Data is the foundation, but don’t let it take over

It is no surprise that data management is foremost in Sprackling’s mind. “All companies,” he says, “should want to have the best data they possibly can. But it’s also true that you need to be very mindful that it doesn’t take over people’s ways of working because you know you can always add an extra attribution.” 

The underlying message is, too often businesses obsess about collecting data without really knowing what they are going to do with it. Does it add value or does it blur the picture? And beyond that, how comprehensive is the data?

He stresses the importance of basic, standard measures: what was sold, when was it sold, was it returned? Those customer touch-points are the foundation for any system. Attributions, customer profiles, historical information all sit on this.

The challenge is to have good data for all product areas: “If you don’t have good data to inform your decision making, it’s hard to operate. Most businesses will have products with a high rate of sale, loads of good data, informing the system and telling you where to put the stock. And there’ll be others which don’t have loads of sales, but maybe it’s something that is always expected to be there by the customer.” Patchy collection would render data on such lines almost useless.

Sprackling goes on to note that some “new technology can just add extra complexity, without adding any value. That’s certainly the worst experience I’ve had implementing new systems. It’s been all great intentions to improve the ability to work at a more complex level. But what it’s ultimately done is slowed down decision making and it’s taken time away from those parts that are probably the most important part which is that range building, that thinking about the customer.”

What good AI in merchandising actually looks like 

The best way to avoid this is by firstly knowing what you really expect from a new system – what benefits are you expecting? – and finding a vendor who will work with you beyond the onboarding process, one who will sit alongside your team, overcoming issues and ironing out any bumps.

“You have some providers who just come across as ‘tech people’. They have a 100% belief in their tool. They think every outcome is going to be perfect. But merchandising is not an exact science, customer behaviour is not an exact science. You want people who can translate what’s happening into the merchandising world. I love a tech provider who says, ‘Yeah, it won’t get everything right.’ People who tell me it’s going to be great, everything’s going to be perfect. I’m always a bit sceptical. I like people who give a warts and all overview of what’s going to happen.”

Sprackling returns over and over again to the need for new technology systems to improve the decision-making process for merchandisers. He doesn’t see it as a replacement for them but as a means of doing their job better. 

“I would see the outcome (suggested by a system) as not being a black and white answer. It should give you a recommendation to accept or not. It should give the time back to the merchandising team to look at the proposed outcomes and then decide whether they’re going to accept not.”

In short, it is taking away the number-crunching and freeing up time to allow a merchandiser to make a positive contribution.  

And Sprackling gives short shrift to anybody who suggests new technology, and especially AI, is a way of reducing head count. He highlights the importance of work-life balance and says that too often teams are coming to the supposed end of their day with an incomplete to-do list. 

It is heartfelt when he says: “There is too much to do every single day. There is too much to do.” 

Getting your team on board  

And he returns again to his theme that a merchandiser’s role is more than allocation and replenishment – even if that is where AI helps best. It’s about understanding the customer, knowing the competitive retail landscape and building ranges alongside buyers and designers that will achieve great sell-through. He, along with most senior merchandisers, is looking for a system that will allow his team to operate efficiently and at the top of their game.

And this, perhaps, underlines the final point: any new system needs the buy-in of the merchandising team. Sprackling suggests this best done by involving the wider team in its development and implementation, as well as by ensuring everybody understands what the benefits are expected to be. In essence, collaboration and good communication.

However, he warns against the two extremes. He believes that neither imposing a system without consultation nor allowing a handful of team members to develop a system will bring good results. The former will create resentment, the latter is more likely to deliver too narrow a programme.

And he finishes with an admission that should be heard by all senior merchandisers: “The big learning I’ve made in the last few years is that not everyone approaches merchandising in the same way that I approach merchandising.

“I find numbers a really easy part of merchandising. And it’s easy to expect everyone else to find that to be the backbone of their kind of merchandising. But actually, if you’ve got a system, it does need to work for all of your team. You do have to consider whether is it going to work not just for those people who love analysing data, who love to really crunch the numbers, but is it also going to work for those people whose strength actually lies in spending time with the product – they’re a bit more about gut instinct when making their decisions.”

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Interested in hearing more of Paul’s gems of merchandising wisdom? Watch the full playlist on Youtube!