⚑
Other integrations
Success Metric Use Cases & Examples
A detailed walkthrough of potential scenarios that Success Metrics can help with
Success Metrics give you the ability to measure just about anything, so let's cover some interesting use cases you might want to leverage for your own metrics. Each use case will cover the same hypothetical scenario, but naturally, you can reuse the patterns described below for your own needs.
Hypothetical scenario ✈️
You are the Customer Success Manager for a product that allows a business's employees to purchase airline tickets for business travel. Every time an employee makes a purchase, your analytics service tracks a Ticket Purchased event.
Active user percent at a customer
Active user percentage is often an ideal metric to start with, as it simply measures the percentage of a customer's users using your product over a recent timeframe.
We calculate every customer's current Active user percent by default, so we only recommend creating this as a separate Success Metric if you'd like to keep track of historical values as well.
Percentage of licenses used per customer
If our engineers are sending a trait along with customers that identifies the number of licenses allowed by the customer's subscription with our business, we can then measure the percentage of those licenses that are actually used over a recent timeframe.
Total airline tickets purchased per customer (last 30 days) 🎫
One of the simplest types of Success Metrics is the total number of events performed by any user at a customer over a timeframe.
Heads up! Vitally will automatically track the total number of times every account has done some event.
Percentage of a customer's users purchasing airline tickets
Measures how common it is for a customer's users to make at least 1 purchase over a recent timeframe. The number of tickets purchased by a single user doesn't come into play here. Note that you might want the denominator to be either Active users at a customer or Total number of users at a customer. The former only accounts for users that actually use your product during the metric's timeframe, whereas the latter will account for all users (active and inactive).
Average number of tickets purchased per a customer's users
Unlike the above user percentage, the number of tickets purchased by a single user matters here, as a single power user can 'offset' the lack of product usage by other users. Note that you might want the denominator to be either Active users at a customer or Total number of users at a customer. The former only accounts for users that actually use your product during the metric's timeframe, whereas the latter will account for all users (active and inactive).
Total dollar amount of tickets purchased per customer πŸ’°
If our engineers are tracking the dollar amount of each ticket purchased when logging the Ticket Purchased event, we can easily measure the total dollar amount of all tickets purchased per customer over a recent timeframe.
Average ticket cost per customer
Again, if our engineers are tracking the dollar amount of each ticket purchased when logging the Ticket Purchased event, we can also measure the average dollar amount of each ticket purchase per customer.
Average dollar amount spent on tickets per a customer's users
Just like the above 2 examples, but instead divides the total dollar amount spent on tickets by a customer by the number of users at the customer, which gives us the average dollar amount spent by each customer's users over a recent timeframe.
Unique travel destinations per customer 🏝️
Now we're getting pretty creative πŸ˜„If our engineers are tracking the user's travel destination when they make a purchase, we can measure the unique number of locations traveled to by a customer's users.
Percentage of a customer's users making any purchase
Let's say our product also allows you to make lodging arrangements for your business travel. We can then measure the percentage of a customer's users that make any purchase for business travel with our product.
Total dollar amount ever spent on tickets by a customer's users
Let's say our engineers track a trait on users that identifies the total amount the user has ever spent on travel with our product. In that case, we can sum those traits up to determine the total amount of money ever spent by a customer. Note that metrics using user or customer traits do not require timeframes.
Last modified 10mo ago
Copy link