Nerding Out to Usage Data for Customer Success

Your product’s usage data is the most powerful data source that a Customer Success professional can leverage.  The data can tell you a plethora of things, from which accounts might be showing signs of churn, to which end users might require training to which features are succeeding or failing.  

While powerful, usage data can be awkward to work with given the sheer number of records you might be working with.  Here, I’ll describe a few ways to dig into the data and easily pull out the nuggets.

Find Quick Wins

Simply exploring usage data can be a complete rabbit hole, this because it’s chock full of data points on your product’s performance, end users’ usage patterns (habits), etc.  It’s easy to “nerd out” to for hours at a time.  I recommend that you identify three or four quick win objectives to focus your exploration.

Here are four ideas that are easy to accomplish and can produce fantastic results:

• Identify accounts that have abandoned your product or whose usage is declining over time
• Identify accounts that are growing fast for upsell
• Identify end users who are not adopting basic, important features
• Identify accounts (or users) with under-utilized features

Get The Right Data

The best starting point is to have data that tells you the who, what, when, where, and how regarding your users’ activity.  I’d recommend that you start with the following fields:

• Date/time (when)
• User ID (who) (pro tip: get the email address so it’s easy to follow up when you need to)
• Customer ID (who) – the account to whom a user is attached
• Event Name (what)
• Product Value (what) – this is applicable for multiple products or modules
• Component Value (what) – this is typically a child structure of product value and may not be applicable to all businesses
• Environmental Variables (where & how) – This data may or may not be useful.  It usually consists of information about the device your user utilized to access your product, such as locale, browser, operating system, and language.  

Put together, the data might look similar to this at the record level:

Put Your Data Into A Tool

In many cases, your product team will provide usage data within a delimited CSV file or a database table.  

The optimal way to explore your product’s usage data is to visualize the data in an application that’s pointed at your data source (file or database)  There are a few favorites on the market, have a look at a few different vendors before selecting a tool.  

No matter what tool you’re using, you’ll want to create tables and charts that summarize events. An example that shows users’ monthly growth rate:

Now that you know what you’re looking for, drill down by refining the time period of the events, with a bias toward spotting recent trends that you can act on now:

• Identify accounts that have abandoned your product in the past <N> days/weeks/months
• Identify accounts that are ready for upsell in the past <X> days/weeks
• Identify end users who have not used a major function in the past <Y> days/weeks

Take Action

It’s not enough to understand what your data is telling you.  You’ll want to do something with it.  

For most of us in Customer Success, the first inclination is to reach out to accounts that are showing signs of churn (this coming from the information you’ve gleaned from identifying accounts with no login action over a period).  

Working with key contacts at your accounts can be pivotal to ensuring customer satisfaction and retention.  However, don’t forget about your end users.  

You might not have the hours in the day to personally engage every end user who is not adopting your product adequately, but you’ll definitely find some that will need your help.  Consider automating that outreach by leveraging your existing training content or knowledge base articles.

Happy exploring!