How many of your customers use your product the way you intend? What percent of your customer base is happy?

As a member of the RJMetrics account management team, these questions are very important to me.

To get this information, I used to manually pull data from a number of different places: our own RJMetrics database (user and event data), Zendesk (support), Salesforce (CRM), Wootric (NPS surveys), and more. This would be great for a moment! Then the information quickly became outdated, and I’d have to rinse and repeat for all n customers. I wouldn’t say this was ineffective, but the thought of having 2n customers was terrifying – there was no way I could proactively help my customers get the most value from their subscription. Something had to give, and so it did.

We decided to build Olga, our home-grown customer health tool. Olga (don’t ask about the etymology) assigns a color – red (poor), yellow (average), or green (good) – to represent the health of our customers individually and in aggregate. The health color for each client depends on the results of Olga’s seven inputs, all of which were carefully crafted by our Customer Success (CS) team. This system allows us to identify exactly which customers are in poor health, and exactly which indicator of health should be addressed. Building a tool like this from scratch was incredibly complex, and the team and I could geek out about it for days. Perhaps I’ll dive into more technical details later, but for now, I want to talk about the why – how the decision to spend three months and a lot of time building Olga was made.

Define ‘health’

The guts of Olga lie in assumptions. What does a healthy customer look like? What does it mean to use our platform effectively? These were two questions that inspired Olga, as well as a number of healthy debates internally. The primary consumers of Olga are on the CS team – people like myself, who are responsible for making sure our customers are happy. We talked about how we want our customers to use our tool, who we think our best customers are, and how difficult it was to gather information about the health of each customer. Eventually, we had a list of seven inputs for Olga – all things that we would look for manually. With the list in mind, we created thresholds and a scale for each category based on our expectations, assumptions, and a little data mining. Now – at a color-coded glance – we can see the health for each individual customer, and for all customers. Does your team have something like this? Did you build or buy it?

It’s also important to note that we built Olga to be adaptable. Our product and customers’ needs change regularly, so we needed a tool that could keep up.

Provide scalable support

You may have heard – RJMetrics was acquired by Magento (the commerce platform giant) in August. As Magento Analytics, we now have the opportunity to bring powerful analytics to > 250k businesses using Magento, and that’s not even our entire market. This poses a challenge to our CS team: How can we better understand and improve our customers’ health at scale? Olga provides much more than insight into our customers’ health – it tells us about how we’re doing as a CS team. If one customer is red in one category, we can apply surgical focus to address that one aspect for that one customer. If we notice a lot of customers are red in one category, that tells us one of two things: our scale is too strict (which happened in the first release!), or we need to make institutional changes (which is happening now). As we gain new customers and our existing customers stay around longer, Olga will enable us to focus our efforts where our customers need us the most.

Wrap up

We now have a better understanding of our customers than ever before. Today, we use Olga instead of manually digging for data, and our daily actions are driven by red and yellow blocks in Olga. On a larger scale, Olga has also helped us improve our service. This tool has produced a wealth of information, it is exceeding our initial expectations, and I have no doubt that the utility will continue to evolve.

If you answered my question about having a similar customer health tool with something other than an emphatic “YES!”, it might be time to start a conversation with your team, because you might need Olga! Post a comment to let me know how you gain an understanding of the health of your customers, or let me know if you’re not yet convinced that this is worth your team’s time. You can also subscribe to our blog to catch future Olga updates!