As touched upon in our blog leading up to this one, end-users drive trends and consumer journeys. Their thirst for readily-available, constantly evolving encounters is quite literally unquenchable. Customised experiences are in higher demand than has ever been the case.
Companies that embrace “disruptive tech” as augmented reality has come to be defined, have the best possible opportunity to remain on the cutting edge of personalization. Augmented Reality can no longer be confined to the ambit of movies or gaming, and paired with machine learning, lucrative businesses prospects are in endless supply. Aspects like computer vision and artificial intelligence contribute collectively to bring AR principles into the “real world”.
Let’s use “search” as the one criterion where augmented reality can truly be a game-changer. Searches have always been text-dominated – you type words into a “search” cache and results are forthcoming. But soon submitting a query to Google by “typing” it became either old-fashioned or too much of a hassle… Some folks even entertain the thought that spelling (or the self-consciousness associated with incorrect spelling) weighed in on the move away from typing to speaking of “voice search”. A voice command is now effectively the norm when using tech – from driving, past Spotify, all the way up to Netflix.
What if machine learning can afford companies the option to implement visual search? A truly convenient and super-simple scenario can now be created. Shoppers could upload pictures to a website and “search” similar items. Through machine learning, computers are able to “see/identify” detail and match related items across a company’s inventory. Better yet, this process can happen directly on the web, in-the-moment so to speak. Now AR can be incorporated to “try on” those items. The level of customer satisfaction will undoubtedly soar along with the amount of data that can be accumulated and repurposed at a later time for frame of reference or re-marketing.
If we forget about the consumer for a moment (just a minute, not to worry) and look at stock and inventory management, the logistical ease that AR brings to the equation cannot be overlooked. Imagine the quality and clarity of instructions that come with/through the aid of AR headsets… Visual order picking, exact object-location and a host of other relevant Intel is available at the “flick of a switch”… and what a switch it could be?! In terms of training the advantages are also valuable as it relates to both curbing of costs and limiting danger. The goal is surely to be able to use the capabilities of ML as the foundation for AR-based, realistic instruction.
Again, the key is personalising and how ML could customise educational experiences designed to take advantage of a specific employee’s current knowledge, knowledge gaps, and best learning practices. Once this foundation is determined it can (and should be) used for further training that assimilates with the job itself. The possibilities are endless, and the technological advances are too great to overlook. It is the belief of Practeria and many other companies like that baseless (and fear-based) stereotypes concerning AR and ML should be eradicated.