Comment: Reimaging merchandising

Can brands use merchandising – one of the most fundamental parts of any retail business – to disrupt the market and get ahead of the competition? The answer is yes, but only if they know what consumers want before they know it themselves. 

This is, of course, easier said than done. Consumers today are increasingly difficult to please. They want brands that share their values and have a clear, consistent purpose. They expect to be treated like an old friend and for their personal preferences to be acknowledged. After all, streaming sites know what we want to watch or listen to, so why can’t stores anticipate our needs in the same way? 

In response to these challenges, we see retailers taking inspiration from the predictive models pioneered by online retailers. This in itself may not be enough.

In our view, the leaders of tomorrow will go further – they will use merchandising to create an experience that keeps consumers coming back again and again. Doing so takes understanding, creativity, and a new level of intelligence in merchandising – something that is made possible by advances in AI.

So how can adopting AI technologies help retailers get better at merchandising? We believe there are three main benefits.

Taking analytics to the next stage

To be clear, AI is not a substitute or replacement for good, solid analytics. However, AI enhances the data analysis that is merchandisers’ stock in trade. Imagine the additional insights you could glean from the vast amounts of data that AI can analyze at speed. Competitors’ current offers, for example, or the complete purchasing histories of every customer.

By crawling online shopping sites, AI can tell retailers what’s popular in different countries, and from social media it can unearth the microtrends that will soon go mainstream. As the stores get more digitised, image recognition and other IoT devices, enhanced via machine learning can detect consumer reactions, shopping patterns and deliver bottom-up insights to the merchant from the field (i.e. the store).

Leading retailers are already combining internal with publicly available external data to identify trends in real time and predict their arcs and longevity using machine learning. They can create customer choice models that predict what consumers prefer to purchase when given specific choices, taking demand forecasting to the next level of precision.

Freeing up the creative, human brain

Merchants can’t afford to be just traders, buyers and planners of merchandise. The paradox of choice consumers face presents the opportunity for merchants to become curators and problem solvers. This can only happen if we relegate the more repetitive tasks to machines and free up merchants to be creative. 

Data may be key to sophisticated analysis of sales trends, but retailers today risk drowning in information. They can use AI to sift through data at great speed, with significantly less human involvement than before.

In so doing, AI reduces the burden of transactional, repetitive analysis, and gives retailers time to work more strategically. One benefit is that AI can support the tagging of item attributes. Being able to populate hundreds of attributes for an item using image recognition and deep learning changes the game on time-consuming tasks. 

Freed from monotonous, lengthy activities, employees have the scope to think more laterally and take a more active role in innovation, customer engagement and other uniquely “human” value-adding activities.

Fine-tuning the experience 

Recognizing that experience is everything in today’s industry, retailers can use AI-sourced insight to give consumers the personalized, responsive service they want, when they want it – whether that’s in the physical store or online. 

One of the strongest ways to improve the digital experience is by drawing on AI’s ability to analyze unstructured data and find exactly what will resonate with each consumer. Retailers can use AI to help consumers find the items that appear on their social feeds, for example, and show how and where to buy them. The retailer that factors this kind of capability into its merchandising will delight its customers, who seek personalization, convenience, and responsiveness.

AI can also make a difference to the physical experience. By segmenting and curating their merchandise to be hyper-localized, brands can reimagine the in-store shopping process. Some are collecting data about their consumers while they are browsing in-store and then predicting what they might be interested in buying. They can then send over retail assistants to help them make the right purchase and make the experience more valuable. 

Faster, more creative, more fulfilling

As big data proliferates, businesses will either be hamstrung by their inability to use it to their advantage, or race ahead of their rivals as they embrace and mine that data for more and more valuable insights. 

Merchandising is going to be more critical and creative than ever, focused on activities that make the role more engaging, energizing and fulfilling—and less administratively grueling. The merchant’s time needs to be spent on bringing creative ideas and intelligent experiences to consumers. Forward-thinking retailers are seizing the opportunity today. 

Innovative retailers are not afraid to challenge which activities can be accomplished by a machine versus those that must be done by a human, and are using AI to differentiate

• FindMine automates the manual process of curating window displays, endcaps and online lookbooks, personalizing merchandising for retailers and shoppers.

• Screenshop uses image recognition to convert screenshots into shoppable results, instantaneously.

• Stitch Fix uses algorithms to predict “frankenstyles” entirely from data, and select relevant items for clients.