Hyperpersonalization goes beyond personalization, as the term implies. Consumers are no longer divided into target groups based on behavior and preferences, but approached as individuals. The use of AI and customer data plays a crucial role.
By immediately processing customer data in the store, AI can even make real-time predictions and make an offer that the customer himself may not have even thought of. The big difference from segmentation into target groups is that hyperpersonalization truly caters to the preferences of individual customers. With that, the offer is much more likely to resonate and increase customer loyalty. The store understands what you are looking for.
Hyperpersonalization in healthcare
This application of AI has clearly already been picked up by business. Market analyses from leading agencies such as Gartner, McKinsey and Piwik Pro show that, despite declining marketing budgets, companies are putting a growing portion of it into analytics, AI and hyperpersonalization. Not only retailers, but financial services companies and even healthcare organizations are looking at deploying hyperpersonalization. Think of health coaches like Welli, the AI coach of the popular weight-loss app Noom. That answers real-time questions and provides advice based on your personal circumstances.
Good advice is always worth considering. Then, as a consumer, you have to be able to assume it is correct. There are still quite a few challenges there in the technology and the organizations applying it. In real-time advice where perhaps several AI agents work together autonomously to pull data from different sources, so there is no longer a human "in the loop" to perform a check. So the data the AI gets to work with must be extremely reliable and not violate privacy rules. The design of the agents behind hyperpersonalization must therefore include solid guardrails (guardrails in jargon) to prevent the AI from using data from unverified sources on its own. These are all issues that management must lay out in solid data governance policies with periodic checks for compliance.
Attention value vs intrusiveness
Hyperpersonalization is more than just another marketing hype and has a good chance of permanently changing the way organizations approach customers. How successful they are in doing so depends on how organizations handle a number of sensitive issues. Customers must be confident that their privacy is guaranteed and that their personal data is in safe hands. There must also be a good balance between attention-grabbing and intrusive advice. And the suggestions must obviously be relevant. This can only succeed with the use of reliable AI models. This is how organizations manage to say goodbye to the "old-fashioned" personalized ads, in which I was offered stuff I had just recently purchased or in which I have no interest at all.
