Webinar Recap: Creating Customer Health Scores That Go Beyond the Binary

Learn about creating customer health scores that go beyond the binary with this recap of Vitally's latest webinar. From metrics to qualitative assessments, see what our panel experts had to share!

It's no secret that Customer Success Teams need the right tools to help them assess and improve customer health. Whether it's tracking customer usage data or making sense of NPS scores, there are plenty of ways to measure customer satisfaction - but what if we could go beyond these binary measures? 

In Vitally’s 7th episode of the Scale or Fail webinar series, our panel of Customer Success experts discuss the concept of creating custom Health Scores for customers that offer a deeper level of insight into their well-being as users of your product. The panelists discussed how to start building healthy scoring models, what metrics ultimately matter when forming qualitative assessments, and much more - so if you missed it, this blog will fill you in with the webinar’s biggest takeaways!

With that being said, be sure to watch our on-demand recording of the webinar! So much more didn’t fit in this blog, so it’s definitely worth a watch. And in case you didn’t know who the expert panelists were in the “Creating Customer Health Scores That Go Beyond the Binary” webinar, we listed them below, so be sure to check them out and give them a follow! 

Question #1: What’s the game-changing optimization you’ve made to your organization’s customer Health Scores model?

Every organization optimizes its customer Health Scores models differently. Whether through a traditional approach or something more revolutionary, it takes time to figure out what model type works best for the Customer Success team and their user base that produces their customers' most accurate and optimized Health Scores. 

Jared: “For us, it was breaking down the different stages of the customer journey and applying a Health Score based on that. It really helped us better understand what's going on with customers, their various stages, and establish triggers based on [their stage]”. 

Jamie: “Backing up your Health Scores with, the very least, notification strategies for the most critical bits are important to customer health [and] directly help you when something is critically wrong,” says Jamie. “It’s important to stay proactive. You can kind of act a little too late when you're waiting for the score to go red. There were probably signals with underlying data beforehand [that could have helped you] prevent that.” 

Question #2: How can you build your Health Score model(s) to ensure they’re supporting different customer segments effectively? Suggestions for how to think about Health Scoring for different customer segments?

The ultimate goal of any Health Score model is to deliver quality insights and data about your customer's health based on their interactions and usage of your service or product. It's not always the most straightforward journey to establish a model, but customizing various customer segments based on maturity is one method that could help you get there. 

Katie: “We launched our maturity curve for b2b podcasting [showing] the different stages [of maturity] starting from the very beginning to the highest maturity level. When we did that, we also used it to align our current customers to where they were on the maturity curve. Just doing that, [we] identified things we were doing wrong.”

Katie (extra quote!!): “[Implementing a maturity curve] was really helpful in understanding why some customers weren't adopting some of these hero features we had launched throughout the year. [In all honestly, these customers] weren't ready for them [because they were at] lower maturity stages,” says Katie. “[Ultimately, we have uncovered more data [with this method] to show us where the risks and opportunities are [with our customers and our product].” 

Question #3: How do you factor qualitative inputs, like CSM sentiment, into a Customer Health Score at scale?

Trying to make sense of customer sentiment at a large scale can be like finding the missing piece in a puzzle. What can you do to turn customer voices into data, and how can you factor it in to create a powerful customer Health Score? How do you sift through mounds of qualitative data and turn it into something actionable? Exploring how to use different qualitative inputs, like CSM sentiment and CSM pulse metrics, with customer Health Scores is key to scale. 

Alexey: “You need to turn [inputs into a] quantitative [format]. This is how you can scale [your customers] up. But there is a huge caveat here because usually, the quality of inputs, especially from your CSM sentiment score, will be different from person to person,” says Alexey. “One person attending the call will say, ‘The customer is happy, [the call] was a good one,’ while another person listening to the recording of the same call will say, ‘No, we have risk here with this customer [and] they are probably not very happy with our products.’” This is a prime example “why you need to strive to start to standardize your system [for qualitative inputs with your teams].” 

Katie: “I love looking at a Health Score, especially a quantitative Health Score, as a baseline and a conversation starter. I typically don't like to initiate a lot of automation straight off the bat based on the Health Score. We use a lot of our quantitative data to fuel our conversations around qualitative data,” says Katie. With the Customer Success Managers (CSMs), we ask them, “What conversations are you having [with the customer] or [what] other points of engagement are you having with the customer? [These answers] help us set the CSM pulse, which we then use to heavily influence the Health Score [of a given customer].”

Question #4: Which types of customer data points impact customer health most, and how can you optimize a Health Score model to depict/surface that?

Figuring out what customer data points are most helpful in predicting their health or making the most significant difference in their overall well-being can take some time to perfect for your org. However, there are various data points to keep an eye on to measure customer health accurately and how to best utilize them to craft a powerful score model. 

Jamie: “Definitely try to focus on what is important to your product and how you measure the unique value of your product. The best way to do that is to put yourself in your user’s shoes and go through your onboarding process flow, through your day-to-day usage, and figure out what features need to be set up to ensure that the product is in a state where it's ready to be used on a daily basis. You need this in your Health Score because if your product is poorly configured, but it's being used every day, it’s being used incorrectly, and your Health Score will actually lie to you.”

Alexey: The number of support tickets can be measured into a customer Health Score, but “how [can you] identify how many tickets is too many? You need to connect [with your teams] and have a conversation about maturity, consumption, and usage. If you can segment your customer by big customers, smaller customers, and so on, you can come up with [pin-pointed details], like how many tickets each customer can open before it negatively impacts our customer Health Score.”

Question #5: How do you ensure that, even with limited time and resources, you are able to put the proper focus on something as important as building out a robust Health Score? Suggestions on where to start?

The first version of your Health Score model will need to be corrected. It's okay for this to have multiple versions and to go on a path of trial and error. It takes some time to identify the metrics that will most accurately depict your customers' health, so it's essential to give yourself some grace and try again when necessary. 

Jared: “Go look at your pricing page, [and ask yourself], what are you selling to your customers? Sometimes we can get really deep into the weeds, so just taking a step back, [and understanding why] customers are coming to us [is a big help],” says Jared. Consider “building Health Scores around some of the features your charging for or that customers are coming to you for. Start small, and then build on it. You're not going to have one Health Score; you're going to have a version two; you're going to have a version three; you're not going to nail it the first time [and that's okay].” 

Katie: "I just dove in, when I got started on our Health Scores, and you know the things that you want to be seeing from customers or that we should be seeing from customers. So make a list of that," says Katie. "It's not one and done. I have iterated our Health Scores at least a dozen times. So get your CSM team involved [and have] an open dialogue [so] you can start to dig in and fine-tune what builds a Health Score [and] what [metrics a] Health Score is made of.”

Question #6: How do you make Customer Health Scores actionable? What steps can a Customer Success org take to make their Health Scores more dynamic?

To really maximize the power of customer Health Scores, CS teams need to take their data-driven insights and convert them into actionable plans. From spotting warning signs before an issue escalates to actively building relationships that keep customers healthy – there are strategic moves organizations can make to get more out of their Health Scores.

Katie: “We like to take our Health Score and align the different usage and attributes with the typical goals that we would see from a customer within that segment. So again, we're looking at maturity curve, a lot of the goals are very similar within the various segments. So, we really look at the usage and attributes that are going to deliver results.”

Jamie: “I think that automation on Health Scores is like static grades, it's tough to get right. I believe the most important thing isn't a trend. [For example, Vitally’s health] scores are on a scale of one to ten. A seven is technically healthy in Vitally, but if it was a ten two months ago, and a seven is not healthy. If it was [under seven] two months ago, now seven is actually pretty good,” says Jamie. Ultimately, “automating on that trend [of historical customer data] is where you can really unlock some next-level workflows, where you're flagging CSMs of concerning changes in historical behavior of the customer.” 

That’s a Wrap

Like what you read? Craving more? Satisfy your curiosity with the on-demand recording of this webinar, and get all the juicy details about customer Health Scores that didn't make it into our blog post! But now that your understanding of customer Health Scores is on a whole new level, why not take an even deeper dive by watching our recording or scheduling a demo with us? You'll quickly see how Vitally can help you build out customer Health Score models that will make your life so much easier.

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