Designing for the average user is a thing of the past. The more personal the experience, the more valuable it is to the customer, and the more successful the product or service is likely to be. Personalization matters, whether it’s a developer console, business productivity application or consumer device. Today, machine learning allows companies to collect and analyze data in real-time. This ability provides a better understanding of the user’s experience with a product, and how they are interacting with other users, products and services. In the next few years, companies will routinely customize the design of their products and services to match the needs of thousands of customer archetypes. In so doing, they will elevate the value of the product to the user population and the business.
AI can tailor every moment and conversation with a customer by learning and using their preferences, behaviors and emotions to shape human-like interactions. Such personalized engagements are designed to get users to come back for more—as much as empower the user with more capabilities. For example, Netflix only has 90 seconds to grab a subscriber’s attention. If they don’t find something engaging in that minute-and-a-half, the risk of them leaving the service increases substantially. AI improves the odds of them staying by serving up the most relevant recommendations for each subscriber.
For example, Aricent helped a financial services firm create a bespoke service that includes interactions based on many personas. At one end of the spectrum is the younger, less financially literate, and less wealthy persona. At the other end is the older, more financially literate, wealthy persona, with many variations in between. The team tested hypotheses and made observations about each persona through data exploration and design research. The result was a production system that could select the persona on the fly and adapt the information provided to ensure the user experience was focused on answering the right questions.