Track Your Customer Health Score to Improve Retention

Why do software marketers need to measure CHS? 

Businesses, such as software providers, that rely on customer subscriptions and other recurring revenue streams are increasingly using CHS.

With expansive software features, diverse customer segments and buyers’ tendency to stay anonymous for as long as possible during their search for software, providers can’t just leave renewals to the customer success teams. The typical process of assessing target accounts or customer segments 30 to 90 days before renewal can be too unreliable and lead to last-minute surprises.

Customer retention plays an important role in marketing as well. According to Gartner research, 36% of technology marketers use customer retention rates to gauge the performance of their team.¹

CHS can be used by marketers to:

• Design content and programs that increase product adoption
• Determine the best time to pitch cross-selling or upselling offers
• Identify customers most likely to advocate your products and provide referrals
• Refine account plans by detecting early signs of customer churn and taking corrective actions for retention
• Increase the revenue obtained from existing customers to expand the use of current solution
• Validate the success of marketing efforts and make smarter decisions about where to allocate resources

Why is CHS better than traditional CX metrics?

To truly understand your customers and their satisfaction levels with your product or service, you need to go beyond standalone traditional customer experience (CX) metrics. For example, relying solely on feedback forms or one-on-one interaction with a customer success manager may not be enough to identify all the problems faced by a particular client or account. Plus, the timing of the feedback also matters; the survey responses may not come back in time for you to intervene for at-risk accounts. 

CHS combines multiple success parameters, including traditional metrics, to give a holistic view of customer relationships, all well within time for marketers to take appropriate action. 

How to measure customer health 

There is no mathematical formula to calculate customer health score. The optimal customer health scorecard for an organization depends on its business needs and the products or services offered. While the information used to develop the scorecard may vary, the approach to creating it remains the same. 

The first step to calculating CHS is to identify the important metrics that would affect your health scores, such as customer support data, last login, customer feedback and net promoter score (NPS). Now, put those data points under a group of key attributes of customer health. Finally, give weightage to each attribute according to your business needs. For instance, if you want to steer product adoption, give higher weightage to metrics indicating product usage rate.

Use score ranges from 1 to 10 or 100, or use color codes (red, yellow and green), with a lower score or red color signifying the need for corrective action, to define good and poor customer health. 

Identifying the key attributes to develop health scores

A customer health score should be composed of relevant, accurate and up-to-date data signals and attributes in order to reflect the true state of health of a customer and provide meaningful insights. 

Ask yourself these three questions to identify the most important attributes for your business and customer health scorecard:

1. What are the kinds of data sources to which you have access?

Every business collects a host of data around customer interaction, product usage and feedback, among other data metrics. Identify the sources of data you have and collaborate with the relevant functional partners to collect the data. Check out the image below for examples of data signals you can capture under different attributes. 

2. Do these sources provide actionable and meaningful insights that are applicable to all individual accounts or customer segments?

Evaluate if the data you have access to is relevant, accurate and up-to-date. Assess what insights your data signals can provide and what desired outcomes they would cover. For instance, if you want to evaluate customers in the onboarding stage, ask if you have sufficient and accurate data for it. 

3. If not, what additional data do you need, and how to get it? 

Improve the relevance of your data by integrating new sources. Capture more information with tactics such as web tracking, surveys and feedback forms. Remember, if you have limited data in the beginning, start with a simple scorecard and build from there. 

Also read: The Different Types of Intent Data You Must Know to Drive Sales

Start small with a simple scorecard

Trying to incorporate many data signals at the start makes it difficult to determine the effectiveness of a scorecard, not to mention the increased efforts that go into data integration. 

Start with a simple model with a handful of the most important data metrics and attributes. As your business and collaboration across departments grow, gain access to more customer data and update your scorecard.