“My smartphone knows what I like and suggests outfits that I will feel good in.”
Inspiration and customer retention play an absolutely vital role. Smartphones give the quickest access to a wide range of products. “These days, users sometimes pop into a shop or browse an app out of boredom, or at least without a specific intention to buy something. They want to be inspired and expect offerings that correspond to their taste and ideas,” Julian believes. The keyword here is personalisation. Machine learning algorithms help to deduce a user’s preferred style or favourite products based on their search terms, their orders and the websites they visit, and then display them in a straightforward manner.
In other words, the shop adapts to each user individually. According to Julian, many users are open-minded towards this: “The current trend indicates that customers are placing more trust in mobile apps and want stores to adapt to meet their personal requirements.” While large online retailers already learn about their customer’s interests in certain products and are getting better at taking them into account, Julian believes that at the moment, smaller online shops are only just beginning to discover this approach.
“My smartphone always knows where the best clothes or products are.”
It’s a familiar feeling - you’re walking down the high street and suddenly you see a fantastic jacket. Or a lamp in a friend’s apartment really appeals to you. The same question immediately springs to mind - “where can I buy one of those?” In the future, to find the answer all you will need to do is open a shopping app, take a photo of the object of your desire, and a few milliseconds later a jacket or a lamp will appear on the screen. Julian explains that the first apps appeared on the market a long time ago, meaning the technology is already quite advanced.
There are, however, still one or two more steps to be taken before this feature becomes mainstream. The technology is still a little shaky in places. “Today, many applications are based on image recognition, whereby the user must still select an object or a section of an image. But image recognition does not always work equally well in every instance,” Julian explains. If, for example, the image not only shows the lamp but other pieces of furniture in the background too, some AR apps can still have difficulties. However, the app expert is convinced that these problems will be solved in the next few months.
“My smartphone doesn’t hold back, and tells me honestly whether an outfit suits me.”
“Mirror, mirror on the wall, who is the fairest of them all?” What sounds like a fairy tale has long since been a reality in technology labs. Let’s look at a relevant test scenario. A customer stands in front of a mirror and selects an outfit. With the help of Augmented Reality technology, the outfit is projected directly onto the customer’s reflection.
Another possible scenario could involve taking a photo while wearing an outfit and letting an app analyse whether the outfit goes together from a stylistic and colour point of view, based on the colours, fit and materials. This also works in the context of buying furniture. Anyone looking for a carpet to match their sofa need only take a photo of it, and the app will suggest suitable carpets based on colour, size and surface. Sounds cool, right? Admittedly, based on its current status, it is hard to say how and above all when this technology will get the green light to go mainstream. It does show, however, what will soon be possible with smartphones and apps.
Thanks to AR technology, deciphering frustrating instruction manuals could soon be a thing of the past. “If someone were to buy a new television and couldn’t work out which cable needed to go in which port, in the future they could simply switch on the camera of their smartphone. This would recognise the device and the connections and show where the plug belongs with a virtual arrow,” elaborates Julian, sketching out a possible development that we may have to wait a little longer to get our hands on.