By Johan Steyn, 25 October 2022
Imagine two-thirds of your company’s revenue resulted from products or services your clients did not know they needed. Imagine you know more about your clients than they know about themselves — if you could accurately predict what they aspire to, their challenges — and the services they secretly wish “someone out there” was able to offer them. Would they buy services they did not know they needed? Could you engineer a need for a new product?
It is possible to outplay your competition if you are able to smartly and responsibly use all the data you are collecting on your clients? Is it possible to achieve more than a 90% conversion rate on customer interactions, leaving the rest of the market behind you in the dust?
In the world of movies and entertainment, the “someone” who saw what others were unable to was Netflix. Almost 80% of what you watch on Netflix is based on personalised recommendations. A typical television programme has an about 30% chance of success, while Netflix’s original content is lapped up by viewers about 90% of the time.
Imagine you could promise your company board, with a high degree of confidence, that a new client offering will be that successful. We all aspire to hire talent that could hit higher targets than others in the market. What if you can hit a target none other realised is possible? The German philosopher Arthur Schopenhauer famously said, “Talent hits a target no-one else can hit. Genius hits a target no-one else can see.”
“Genius”, in our time, is a result of hyperpersonalised client offerings based on efficient and predictive use of the mammoth amounts of data we harvest on them daily. It is possible to predict the “novelty patterns” of your clients just like Netflix does. Most of the content their viewers consume is a result of the Netflix Recommendation Engine (NRE).
They are able to cluster people who have the same viewing habits and preferences, using machine learning that their resulting predictive algorithms use to create “taste communities”. The NRE filters more than 3,000 show titles and 1,300 recommendation clusters at a time for about 195-million users in more than 190 countries. This makes it easier and quicker for customers to locate the shows they desire to watch.
Netflix is able to comprehend the psychology of its clients thanks to the data it collects. It can thus modify its customers’ experiences by employing landing cards: images or video trailers customised to what the individual clients would most likely click on.
Since Netflix predicts that its original shows will be successful, the firm has created more than 10 distinct trailers for each piece of original content. They place landing cards into these trailers for clients whose interests align with this content, ensuring that the relevant audience receives individualised recommendations and customised imagery.
You may wonder if your company can be like Netflix. If you collect the needed data, use algorithms to analyse it and build behavioural predictive models, you certainly can. The technology already exists.
We need to move away from a one-size-fits-all approach to customers and embrace the new era of hyperpersonalisation. It is very possible and greatly needed.
• Steyn is on the faculty at Woxsen University, a research fellow with Stellenbosch University and the founder of AIforBusiness.net