From scoring health to predicting outcomes - involve.ai's Renewal Index

Health scores are everywhere and for good reason! Any business interested in growth wants to track the well-being of its customers and take action if their health is poor.

But what if health scoring is already archaic? At involve.ai, we are ready to move beyond health scores and simply arm your business with revenue predictions.

What is a health score?

For the uninitiated, health scoring is a method of tracking whether an organization’s customers are successfully adopting its products or services and feeling satisfied with their spending. It can be managed in a variety of ways. Some organizations simply rely on Net Promoter Scores (NPS) or other Customer Satisfaction surveys, but many create scores by combining a number of measures. Often, these scores are managed manually by Customer Success, Renewal, or Sales teams. In all of these cases, scores are typically imbued with different unconscious biases and lack consistency and automation.

A number of CS platforms in recent years have improved health score creation, standardization, and management, and involve.ai’s early warning system has taken that a step further through AI analysis and automation. However, if AI can make a health score predictive, do teams even need the score anymore? Or do they simply need to understand the outcome if a customer’s behaviors and sentiments continue down a trajectory?

Are customer health scores a thing of the past?

Not necessarily. Most Customer Success platforms will still work toward improving and automating health scores, and they may continue to be helpful for CS professionals to manage their customer relationships. BUT! We at involve.ai don’t see health scores, per se, as the future of early warning.

Instead, the involve.ai platform will be moving away from health scores in the new year and replacing them with a renewal and upsell index. Rather than a 0-100 score, these indices will take the early indicators of customer upsell and churn, benchmark them across segments, and predict (with greater than 90% accuracy) customers’ likelihood of renewal. In short, rather than scoring a customer’s current health, these indices predict future revenue outcomes, allowing teams to reinforce and ensure positive outcomes and intervene to prevent negative ones. They will allow Operation and Revenue teams to accurately forecast and CS teams to take quick, prescribed action rather than working out whether a customer is at a health score of 65 or 70 percent.

How AI models will predict renewal and revenue opportunities

Today, involve.ai’s patented machine learning models analyze customer data to determine how much weight specific behaviors and sentiments have historically had on upsell or churn. They then apply these insights to current behaviors to assign a health score that predicts a customer’s likelihood of churn.

Because this health score is already predictive in nature, the way the models work to assign health is not changing, only the way that we are labeling it. Instead of delivering a health score, the new index will alert teams to a likely outcome in a clear statement, along with recommendations for action.

We’d love to show you how. Book a consultation with our team to learn more about how we work and why!