As long as advertising and relationships between customer and businesses have existed, certain terms and expressions have come to escape the chains of industry jargon and superimposed themselves within populist lingo. In doing so, they have captured both the spirit of the times and lost much of their original meaning. So what is the difference between talking about beauty personalisation technology and actually doing it?
Currently, there is plenty of this to go around, perhaps more so than ever before: for example, companies that preach sustainability while in fact being guilty of cynical greenwashing for marketing purposes, or those that suggest that they are the true purveyors of tech innovation, just as much as companies that market themselves as using artificial intelligence or machine learning and beauty personalisation when, in fact, it’s nothing more than a smoke screen for business as usual.
Firstly, there are the large quantity of companies that say that they do beauty personalisation but either don’t go far enough with it, or aren’t doing anything that resembles beauty personalisation technology at all. The customer heads towards these sites in anxious anticipation of a shopping experience that feels unique to them, but are then sorely disappointed to find that there is either too much choice, leaving them to sorrowfully wonder if someone out there could please personalise the personalised selection offered to them, or that the personalisation relies purely on very basic decision trees that don’t really account for their lifestyle or personal needs.
If brands made more advanced decision trees, combining the ability to collect more significant information about the customers needs with a simpler and friendlier user experience, and then added machine learning on top of that, they’d soon see that the customer is not the only one to benefit.
Another aspect of tech innovation that had, at one point, certainly seemed to take the beauty personalisation industry by storm was the use of selfie based tools to govern what products a person should use. Most of these selfie based tools are really nothing more than a gimmick, suggestions changing based on lighting, time of day and angle at which the selfie is taken in the best case scenario, or only scanning for the most basic of clues, usually based on racial appearance, and hitching their bets.
This is something that has increasingly been recognised by the beauty retail and cosmetics industry. It is also worth noting that those apps that may indeed be able to spot acne or dry patches, and so account for them, also tend to consider white skin as the norm that ethnic minorities (especially Black and South Asian) deviate from, meaning that the experience doesn’t work for them at all. As a lot of these technologies are not optimised for every skin tone, you’d be hard pressed to find a single non-white face used to illustrate the product, which leads to a negative and discriminatory experience. Beauty personalisation technology ought to combat this internalised prejudice.
Beauty personalisation technology ought to put the customer’s interests, and so their likelihood to buy, at the foreground, and do so in a way that actually delivers concrete results. It’s more than just a buzzword designed to attract customers, hoping that they won’t just leave again once they realise the product doesn’t really do all that much.