Imagine walking into a store looking for a dress or shirt from one of your favourite brands. Sometimes we may see something in the window, but most often we will walk rather aimlessly, wondering what is new. Then we might look for items we will look good in and whether these are available in our size. We may also consider which variation of colours, design and fit we would like to have and which of these options are available.
Today, most of this type of ‘searching’ activity is made possible by a shop assistant you got to know well over time. Or an assistant that annoyingly asks every five minutes whether you need help. Meanwhile, you may not even know what you are looking for. Yet within an existing system, and activated through a garment label embedded with the latest technology, lies the foundation that eliminates many of these mundane issues. The very label can direct you to the best options available for purchase. It can reflect new colours of the same garment on a screen, or show you the latest designs in the garments you wear often. It can show you which colours, other pieces of clothing and accessories will go well with the suggested options. And it can do this in a subtle way that directs you to what you are most likely to buy. It can also indicate which consumers often buy many items, as opposed to those that buy only one special item at a time. Or consumers that spend very little time in a store, and those who love to wander around looking at a wide array of options.
As algorithms grow and become more representative, it will begin identifying groups of people with similar tastes, groups of people who are always looking for new designs and new fabrics. And it can do this at a microlevel – one individual at a time. Already at this point in time, there are experiments being undertaken in many stores to test these concepts, but these are often rather anonymous, not personalised.
The consumer still has to find and select the right garment, take it down and then look at a screen reflecting them wearing it. Yet, with labelling technology like RFID and other new developments, this process can be entirely personalised. Never redundant. Always subtle. No irritating or undertrained shop assistant asking the same questions over-and-over again.
Together, the consumer and the label technology are what activates the personal experience. It enables all consumers to have a personal experience which will leave them feeling valued and appreciated. That is not to mention the potential of machine learning, artificial intelligence, robotics and biotech fabrics. Yet, to be thinking in this direction, we need to see everything as a carrier of data that can speak to every other carrier of data. Labels are a central source of data, both practically and experientially. While today it is estimated that 70% of digital technology is used for logistical purposes, the future is wide open for garment brands to create exceptional customer engagement with something as simple as a label with embedded data, supplemented with their existing hi-touch improvements and engagements. Hence, there is an important interface in how garment label technology is applied and combined with staff aptitude and training, store layout and merchandising, stock constitution and customer data.
Whilst the underlying consumer experience design is a vital ingredient, the brands and retailers who are willing to experiment and disrupt, are those who will overcome the threat of online retail. Even more so, the ones that can successfully combine online and offline, will be unstoppable. Yet, to think this way, we have to realise a label is not just a label. It is a carrier of data that activates whatever other data point we want to activate with it.