Let's start with personalization. Personalization is tailoring the tools, services, and goods workers use to their unique personalities. At the lighter end, this can be achieved by mapping characteristics that describe a person (e.g., age, seniority, geography, affinity). Think about how a product’s front-end may be different if the sign-up process elicits these traits (e.g., a different landing page for people from different countries, different music or film recommendations).
Hyper-Personalization is taking that to the next level. If personalization is a tailored suit, hyper-personalization is a bespoke suit. Hyper-Personalization goes further by matching a user’s experience on categorically unique traits, elicited by their behaviors, interactions, and individual characteristics. Imagine common office software solutions and data portals that understand you and your workflow.
The promise of hyper-personalization in the enterprise is all about overcoming some of the current obstacles knowledge workers face, sometimes without even knowing. Take two current problems: diminishing productivity gains from software and data access, as well as systems overload. On the former, we've enjoyed the tailwind of 30 years of software digitization. Our workforce is familiar with tools like Microsoft Office and increasingly familiar with more technical tools like Python and Relational Databases. However, the same productivity gains we reaped years ago from adoption have petered out. To combat that, we have increased the number of solutions deployed inside of a firm.
According to a Statista survey, the average amount of “Software as a Service” solutions deployed within a large company has grown to 130. This has its limits, as context switching and learning each solution's unique user interface and workflow has its limits. But if these tools adapt to the individual instead of the other way around, we may be able to unlock another leap forward in productivity gains. As such, personalization is the key to unlocking greater efficiency, better quality work, and more productivity from enterprise applications and datasets.
AI can push the right information to the right worker, based upon their unique access to software and data, and it can tailor it to their workflow. That is the promise of Unprompted AI. Doing so requires a knowledge graph of the worker, often crafted through their digital twin. Doing so unlocks so much data, tooling, and knowledge at the enterprise worker's disposal. It improves ROI on existing data spend, and increases productivity while creating a more human-centric approach towards the integration of AI into our work lives.
Read ModuleQ's personalization white paper here.
Hyper-Personalisation: The Next Frontier in Digital Transformation (IBM, 2024)