Hyper-Personalisation, simply put, is when different types of technology and data come together to adapt the userexperience specifically for every individual customer. This means that Hyper-Personalisation is tailored around the customer’s habits – where they are engaging, what they are buying and how they want or choose to experience a company’s service. What this also means is that today’s audiences are exposed to an information overload. More so, the rapid evolution of technological trends means that industries need to adapt to keep up; processes need to be streamlined to increase productivity and eliminate procedural gaps whilst increasing the overall profit line. Hyper-personalisation is therefore more than just the latest buzzword, it is a targeted approach, built off data specific to a person, to cater for a specific requirement.
One of the biggest and likely most viable next steps in any development strategy would be to consider the introduction of a knowledge-learning programme. There are currently multiple iterations of this which have proven that using a form of machine-engineered approach can significantly improve the hyperpersonalised experience.
Convenience has instigated a deeper drive for hyper-personalisation in creating expected brand optimisations at an exhilarated rate
Using these data-driven programmes enables the provision of a real-time system metric, generating product offerings, responses and discounts per customer in their respective experience process. This is easily achieved via the programme’s ability to learn in response and create large data-mines by which algorithms can be built to suit consumer profiles. The simplest example of this would be Chabot’s, which man everything from social media direct-messages to website landing pages, thus offering real time solutions to pre-empted enquiries.
This goes a step further in predicting scenarios based on inanimate actions. While it’s still being slowly rolled out across Africa, Uber has introduced this level of intelligence via their Ride-Check safety feature. This feature identifies when a trip has been stationary for a questionable amount of time, prompting a call to ensure the rider and driver are safe.
The Convergence of Convenience
This type of hyper-personalised interaction brought about through technology and real-time data has given rise to the consumer accustomed to ease, affordability and most of all convenience. To tier the principles of a potential purchase, convenience will most likely rank as a priority. The modern day life is a busy one often laden with excess information, so any way to minimise the daily administration of tasks is welcomed – think of this as the Siri of everyday life.
Achieved via the use of big data, there is now a need to have online footprints mapped, studied and configured to reenergise targeted efforts. Every day, consumers leave sums of key insights with any online activity, which in turn creates large data mines. Using these data mines, brands are able to build and scale multiple products, offerings and subsequent campaigns that are specific per an individual; it’s almost as if no two adverts projected are the same. This is becoming the fingerprint of modern business communication and it has only just begun to scratch the surface of machine learning and the convenience it brings.
Convenience has instigated a deeper drive for hyperpersonalisation in creating expected brand optimisations at an exhilarated rate. What this essentially means is that customers want what they want, and they want it now, made specifically for them in a matter of minutes. At its most basic, one can consider services like Netflorist which offers personalised gifting delivered within a day or two. Also, Uber Eats offers a personalised approach to food by allowing eaters to specifically alter their meal to their preference, delivered in under 30 minutes, just by a few taps of a button. The ease of this more often than not results in repeat usage.
Hyper-personalisation in Africa
When looking at the world in comparison to Africa, there are significant differences with how societies have evolved. The (almost) common denominator however is technology, as the gap isn’t as wide. In Africa, many businesses are already using the tech-driven criterion and successfully operating in the fourth industrial revolution. Hyper-personalisation allows for localisation of product and service offerings, making it tailored to both the region and citizen, like uberBODA and uberPOA, Uber’s motorcycle and TukTuk products respectively, available in East Africa.
There are however some issues which slow the progress of Hyper-Personalisation, including the considerably high costs of bandwidth and the price associated with knowledge-learning and data-driven technology.
While the gap is closing, it isn’t at a rate many prefer. This is especially true for the end-users who have already acclimatised to first-class service. Individuals want an Operating System for their daily lives, providing services that they normally wouldn’t want to do, but need to. Uber takes the driving out of getting from A to B. Netflix takes the buffering out of streaming. Uber Eats makes food for all occasions and taste buds, in any location. It’s all about giving the customer what they want, when they want it, specifically built for their individual profile.
In order to deliver this type of super specialised product, more than just technology is required. What’s needed is an innate understanding of a product’s user-base. It’s an exciting time, as technology now empowers the user, maybe more so than the brand.