Answer
AI enables more sophisticated customization of health scoring models, allowing businesses to define and weight metrics such as product adoption, ticket resolution time, and survey scores based on their unique needs, with models continually refined as AI learns from customer interactions to ensure the health score adapts as the customer journey evolves.
Customer preferences change over time due to market trends or new competitors, requiring models to be monitored and retrained regularly to avoid performance degradation. The more data you have, the more accurate the predictions will be, as the models are constantly re-trained on your data, meaning accuracy improves over time.
Customer feedback about the accuracy of AI predictions gives the score a label, which is then analyzed by machine learning to improve the scoring model, with each new bit of information creating a more refined model. The more data the AI analyzes, the smarter and more efficient the onboarding becomes over time, introducing a layer of continuous improvement rather than relying on occasional surveys or manual reviews.