Customer health scores are an essential metric for understanding your customer relationships. When used effectively, they bring valuable insights into customer satisfaction, risk of churn, and potential growth opportunities. However, reliability is a common issue with customer health scores. Customer-facing representatives often admit that they do not devote much attention to customer health scores due to the perceived lack of value they bring to their work. Here are five checkpoints to ensure you implemented health scores the right way.

Ensure data is up to date

The first thing to think about when talking about reliability of healthscores is data accuracy. Using outdated or incorrect information results in misleading health scores, which further leads to misguided actions. By implementing systems that automatically update key data points such as product usage, support interactions, payment history and other relevant information, healthscores become up-to-date and relevant. 

Additionally, you should schedule a regular audit of your data sources to ensure that they are feeding accurate and timely information into the health score.

While regular updates may seem as the obvious first step of a healthy health score, companies often manage to get it wrong due to inadequate IT support, using legacy systems that can’t connect to the health score calculator or underestimated need for computing resources that brings health score calculations to a halt.

To ensure the best implementation, it’s recommended to check accessibility of all the necessary systems prior to implementing health scores.

Implement Prescriptive Analytics

A customer health score should not only reflect the current state but also guide future action. A properly set up health score consists of a variety of factors like the product usage, contract duration, demographics and similar information. It makes sense, that based on the variety of factors in the score, there should be a variety of next steps to increase it as well. Without a proper explanation, the health score by itself is useless.

Imagine two customers having a health score of 45/100. The first one is a regular service user who had technical issues in the past quarter and called support multiple times, and that decreased the score due to recurring issues. The other never got into touch with support, but also, hasn’t been using the service for the past 3 months. Same score, very different next steps.

That’s what prescriptive analytics are about. Moving from the question of what is the score, to answering what should be done to improve it.

For example, if a customer’s health score is low due to a decline in product usage, the guidelines might recommend personalized training sessions, additional support, or a product usage review. Technical issues on the other hand, after resolved can additionally be handled with addition of discounts, lowered rates or free-of-charge premium services. Treatments should be standardized but flexible enough to be tailored to individual customer needs and simple enough to execute for any representative that gets in contact with the customer. 

Schedule Regular Health Score Audits

Health scores are not a set-it-and-forget-it tool. Regularly scheduled reviews of health scores and accompanying recommended actions should be an essential part of your customer success process.

These reviews allow you to reassess the factors contributing to the score, identify trends, and adjust your strategy as necessary. Whether it’s monthly or quarterly, having a consistent review schedule ensures that you catch potential issues early and can act proactively. Furthermore, while deploying a new feature, it’s commonly overlooked adding its usage to health score calculations. With common health score audits, product teams get aligned more quickly with the customer success, and both teams are kept up-to-date on the impact the new features and campaigns have on the customers. Here’s a few ideas on what to check during a Health Score audit:

• Data sources – are all data sources active and relevant? Were there any product updates that changed the way certain databases should be handled?
• Data latency – is health score getting updated in a timely manner? Are all updates done fast enough to make a difference?
• Health score reliability – does health score on average reflect a true state of customers’ behavior? How many highly scored customers churned in a period of time?
• Health score usability – how do different teams rely on health scores and what are their inputs on what would make them more useful?

Train Customer-Facing Teams

For health scores to be truly effective, customer-facing teams must be well-trained in understanding and using them. Creating intuitive dashboards that properly reflect the customers’ state and give meaningful feedback on the best course of action is of course a major help, but it’s still up to a representative to make the best use of the provided information.

This training should include how health scores are calculated, what they indicate about customer relationships, and how to use them to drive customer success initiatives. When your teams are confident in interpreting health scores, they can take more meaningful actions to improve customer outcomes.

One way to ensure customer-facing teams are confident in the use of health scores is to keep them in the loop during the initial implementation, reviews and updates. They are usually the first ones to see discrepancies between the health score and the true state of the customer, making them a valuable part of ensuring health score reliability.

Next steps

Customer health scores can be a powerful tool for driving business success, but only if they are reliable. By ensuring up-to-date data, establishing clear guidelines for improvement, defining the components of the health score, scheduling regular reviews, and training your teams, you can transform your customer health scores into a reliable and actionable metric. In doing so, you’ll not only improve customer satisfaction but also drive long-term customer retention and growth. If you need help with auditing your health score and implementing latest data engineering methods into your customer lifecycle, get in touch with us.