A customer health profile allows you to track the health of your customer relationships. By understanding the health of your customers, you can identify at-risk accounts and take steps to prevent churn.
As you build or rebuild your customer health profiles, consider the following best practices and examples.
Getting started with health design
When structuring a customer health score profile, it is important to consider the following best practices:
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Use a variety of input categories
Customer health is a complex concept that cannot be measured by a single metric. Instead, it is important to use a variety of input categories, such as usage data, support tickets, and customer feedback. -
Weight input categories based on importance
Not all input categories are equally important. Some categories, such as usage data, may be more indicative of customer health than others, such as customer feedback. -
Use as many automated inputs as possible, but prioritize change management to execute on manual field updates required
The more automated fields used the more likely you will see higher adoption of the customer health score, but manually-updated fields should get updated. Change management best practices and leadership accountability is essential to proper adoption.
Health profile examples
The following are examples of customer health score profiles that you can use a reference point to get started or to refining your existing customer health score.
Example 1
For a high touch or traditional engagement model, you might consider the following input categories:
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Relationship
How often do you engage with the customer? How often do you have strategic touchpoints like a QBR? How many champions do you have throughout the org? -
Commercial
A more holistic approach to looking at usage. If you have fewer usage data points, you can leverage expansion opportunity tracking to measure growth and likelihood of renewal. -
Sentiment
Subjective input by CSM and/or AM -
Risk Factors
Proactive tracking of specific identified roadblocks, data/integration challenges, and volume of support tickets. Risks and data issues will need to be manually updated.
| Relationship | Commercial | Sentiment | Risk Factors |
| Last client meeting/call | Usage Data | CSM Sentiment | Risks (picklist) |
| Last QBR Date | Expansion Opps | Likelihood to Renew | Data Issues (picklist) |
| Champion Count | Last renewal Date | # of Support Tickets |
Example 2
For a low touch or scaled engagement model, you might consider the following input categories:
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Engagement
How active is the customer? -
Product Value & ROI
If you know that successful customers achieve a specific outcome that is trackable, measuring and tracking this is an incredible health score input. -
Product Usage
In this example, multiple product usage data points are being used. This will vary from company to company. -
Advocacy
Based on NPS feedback from key stakeholders and whether they would provide a reference for new business.
| Engagement | Product Value & ROI | Product Usage | Advocacy |
| Last login date | Outcome Metric | Usage Data Point #1 | Most Recent NPS |
| # MAU | Usage Data Point #2 | Referenceable | |
| Usage Data Point #3 |
Ongoing iteration
Once you activate your health profiles, we recommend that you periodically "tune up" profiles based on team feedback and evolving patterns within your customer behaviors.
Avoid making daily or weekly adjustments to health profiles. Teams learn to rely on these profiles to make data-driven decisions, so it's best practice to communicate changes in advance.
We recommend the following:
- 30 days after initial rollout of Catalyst
- After significant product changes
- Significant business or engagement model change