Customer account health is a data-driven metric to identify whether your customer is getting value or not. According to a popular survey, maintaining a customer health score was more predominant in organizations with a less than 5% gross churn rate. Although the survey doesn’t identify a lucid correlation between customer health scores and revenue generated through upselling or cross-sell. 

However, it shows a big impact on forecasting renewals and having a better clarity on the CSM role. A study has also found that 46% maintain a customer health score to forecast churn or renewals.

Defining an ideal Customer Health Score requires taking consideration into various elements. The traditional form of Health Score was calculated as a single score that eventually failed to demonstrate the accuracy of the customer’s health at a given point. A single customer health score is a bluff. As health never comes in one shape and form. There have to be multiple dimensions to health. Multiple dimensions when considered together provide an accurate Customer Health score. Various dimensions of it should comprise-

What are the assorted dimensions of Customer Health?

1. Financial Health: Gives an account of the purchase history, overdue invoices, purchased license, canceled license, etc.

2. Relationship Health: It measures how frequently contact has been established through touchpoints. Like, the frequency of communication of the CSMs with clients, and their rapport with the stakeholders.

3. Product Adoption Health: It simply measures the Product’s Stickiness. As example, the Adoption of the core features, active login days of the client, hoe frequently your product is getting used.

4. Service Health: Defines a transparent idea about the effectiveness with which your support team handles customer issues. For example, the number of tickets raised, and the number of tickets resolved. Therefore the happiness quotient of the client.

5. External Factors: Positive confidence tags, for example, If the customer is driving a case study with you, if they have referred anyone, etc.

A better form of Customer Success Technology will allow you to live the customer’s data at every interaction from product usage to the financial status of an account, and the high-level risk count, to extend the efficiency and therefore the effectiveness of your customer support system. However, there are a few elements that you need to consider while setting up the Customer Health Score. To jot down, the best practices include-

  • Monitoring the correct metrics, i.e., don’t mix support signals with product adoption signals
  • Measuring leading indicators with short lookup windows
  • Having an easy risk strategy, i.e., the poor score should be broad and should take into account each churn signal separately.
  • Acting on poor leading metrics till health score is good
  • Regularly refresh your configurations (recommended periodically every 3 months) on the idea of new learnings.

Major Reason why Customer Health Score fails?


Most often Customer Success teams don’t put much attention to the look-back period while calculating the account health. This could be a significant reason where the major problem arises. Let’s take an example.  Imagine you have set up a customer health score for which an account to be in good health, the customer has to mark certain touchpoints in the customer journey. For example, they should have started doing more campaigns, should have started adding new users, or whatever your technology enables your customers to do. In this scenario, the look-back period could be one day, one month, 90 days, or perhaps a year that may entirely depend on the type of problem your product is solving.

Now, the key point, you should note here is that the longer the look-back period, the more likely you’re to get a false positive. For example, if the customer was using the product effectively in a look-back period of 90 days. Certainly, in the 90th day you might still be getting very good health of that account whereas, in the last 89 days, the customer might have simply stopped logging in. So you should keep the look-back period, as narrow as possible in order to avoid false positive results.

The key to putting in a successful health score is to balance the look-up period as short as possible. A typical approach is about two weeks, but it can very well depend from customer to customer.

What is the solution?

A very basic thing to know here is that there are various dimensions to the overall Customer Health than having information on how your customer adopts your product. Lots of CSMs remain in the misconception of using only product adoption as the key metric to decide the health score. We should consider other dimensions like Relationship, Service, Financial and Subjective opinions/External factors that may act as leading indicators as mentioned above. To craft an effective and accurate Health score, one has to consider various metrics of Health Score that are important to your company, product, and customers.

Some of them are mentioned below:

  • Overall Product Usage
  • Product Upgrades and Renewals
  • Community Engagement
  • Marketing Engagement
  • Frequency of website visit
  • Customer Support Calls
  • Customer Feedback
  • Product feedback
  • Survey results

The new age technologies like AI (Artificial Intelligence) and ML (Machine Learning) are enabling advancements to reduce the pain and effort of a CSM in many ways. In fact, this technology is helping to predict and draw a perfect health score for customers.
AI and ML technology will help you draw a health score that is significantly reliable to give actionable insights to improve customer experience.

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