Scoring user health may sound like medical advice, but it’s actually a vital part of understanding your customer base. As the name implies, users are assigned scores based on their behaviors and interactions with your product. Scoring individual users based on specific criteria for your company and industry may sound granular, but it can help you identify problem accounts before they leave.
What Is A User Health Score?
A user health score is the likelihood a user will achieve your desired result. That desired result could be a purchase, regular usage or upgrading depending on your industry and model.
So if you are scoring users based on the desire to keep them as lifetime users, they would have a higher score if they recently renewed their subscription.
Metrics Associated With User Health Scores
Examples of metrics by which you can score your users:
- Product usage
- User feedback
- Marketing engagement
- Website activity
- User support cases
- Product upgrades and renewals
- Community participation
The Importance Of Scoring
Scoring your users helps account managers and customer success teams monitor your company’s user base. User health scores can provide an early warning system to account managers when users are at risk of churn. High user scores across the board indicate that user needs are met, and your product is working well.
Additionally, high-scoring users are more likely to recommend your product or service to their friends and family, increasing your net promoter score (NPS). They may also recommend your company on social media.
How To Create A User Health Score
Creating a user health score can be time-intensive so consider these important factors before delaying. The score usually indicates the likelihood of the user ending their account with you and switching to a competitor.
You’ll want to keep in mind the speed at which a single user can significantly change their score and which metrics make up the score.
Define User Health
This is a tricky step because user health can be subjective. You can take some of the guesswork out of it by using product engagement metrics, and how often the ideal user purchases your products or services. But understand there are always extenuating circumstances that cause users to behave unexpectedly.
You can also consider other metrics like user feedback and engagement with social media campaigns, depending on your company and marketing strategies. The important thing is to decide whether the compiled metrics should be given equal weight in a score or if some are more illuminating than others.
Select Predictive Metrics
Your industry and products or services offered will heavily impact the metrics that you value the most. Many companies include metrics like the ones listed above plus others such as user retention cost, net promoter score, and service renewals.
Once you have selected your metrics, analytical tools like Kissmetrics allow you to measure user interaction with your website and are ideal for compiling data.
Create A Scoring System
With your predictive metrics in mind, you’ll need to decide how much weight to assign each metric. For example, knowing that a user called to clarify installation directions and another user left a scathing review on your website shouldn’t be given equal weight during engagement scoring. A support case doesn’t necessarily mean your user will churn, but a nasty review likely does.
Develop A Health Score Scale
Depending on how you define user health, one type of scoring system might stand out as better for your purposes. For example, if you decide that user health is solely defined by whether a user has renewed your service within the past 12 months, a color code system would work perfectly.
We don’t recommend using a single metric to determine user health since it is a complex concept that requires multiple metrics working together to provide an accurate picture.
Weighting and scoring various metrics will usually leave you with a numerical score for each user.
Visualize User Health Score/Strategize
Now that you have a method of scoring your users, you should next decide how to present your method in a straightforward, meaningful way. We recommend consulting with your customer success and account management teams to see how they prefer to visualize the data.
User health scores increase in value as you add more buckets. Increasing specificity makes it easier for account managers to know at a glance how users score. We list some examples of user health scoring systems in the next section.
After you’ve selected appropriate buckets for users, you’ll need to strategize with your teams. Choosing strategies to assuage user dissatisfaction is crucial for retaining users, although individual strategy will depend on your company’s industry.
This might look like offering unhealthy users another onboarding, discounts, or a free trial for a higher tier of subscription.
Examples Of User Health Scores
There are a variety of ways to score user health. Depending on which is the most meaningful to your company or, if there’s an industry standard, you’ll likely choose one of the following common examples of user health scoring systems.
A percentage scale is the most specific of the examples listed here. For example, an account manager automatically knows that a user who has scored 32% is more dissatisfied than a user with a 45% score.
This makes prioritization easier, although it provides many buckets of data that might be harder for customer success and account management teams to parse quickly.
Many companies prefer to use the stoplight system, which simplifies user scores into Green, Yellow, and Red. While this system is easy to remember, it might make things too simple.
A user who has renewed in that timeframe would be “green.” An account manager who had persuaded a client not to cancel would score them “yellow,” and a user whose subscription had lapsed would be coded “red.”
Account managers would know to prioritize users marked Red, but there aren’t degrees of Red, making it difficult to distinguish between levels of dissatisfied users.
The alphabetical scale works similarly to the American grading system in school. Users are scored with a letter between A and F, with A being the highest score and F being the lowest.
Like the color code, the alphabetical scale is easy to remember and gives account managers an instant visual of how they should interact with a user’s account.
As the name implies, the ranking scale compares each user’s score to every other user’s score and creates a ranked list. This can come in handy when you’re looking for the lowest-ranked users to provide some kind of intervention and prevent churn. It might also be an opportunity to reward high-ranking users with a promotional discount.
The downside to the ranking scale is that, like the percentage scale, it doesn’t inherently provide convenient buckets for customer success and account management teams. Instead, they have to do some reading and sorting to find the valuable information.
Other Metrics That Indicate Overall Company Health
In addition to the metrics listed above, the following metrics can also give you a good idea of your company’s general wellbeing:
- Churn Rate – a measurement showing the number of users who stop using your product or service over a specified period.
- Average Revenue per Account – the total revenue earned during the specified period divided by the number of active accounts.
- Net Promoter Score – surveying users on how likely they are to recommend your company to a loved one on a scale of one to ten (with one being the lowest and ten the highest score).
- User Retention Cost – the total needed to persuade a single user to continue purchasing your products.
- User Satisfaction Score – surveying users on how satisfied they were with their experience with your company or with your company’s product on a scale of one to ten (with one being the lowest and ten the highest score).
- Customer Lifetime Value – the total amount a single user is expected to spend on your products or services throughout their relationship with your company.
- Monthly Recurring Revenue – the average revenue per account per month multiplied by the number of accounts in a given month. This is an estimation of how much revenue your company should expect to earn each month.