Success Metrics

Success Metrics are custom KPIs defined using the data you feed into Vitally and calculated for each of your accounts.

Success Metric Overview

Success Metrics are custom KPIs measured for each of your accounts. They are powered by equations you define, which can take into account almost any of the data you pump into Vitally, including product events, account and user traits, total users at an account, and more.

Success Metrics help you to define KPIs specific to your product and business. They are great for measuring:

Number of product events created by an account over a rolling timeframe (e.g. number of User Invited events over the last 7 days)
Percentage of an account's users performing specific event(s) over a rolling timeframe (e.g. percentage of users that have performed the User Invited event over the last 30 days)
The percentage an account has used of some feature/component they are billed for (e.g. percentage of pre-purchased licenses used)
Changes in a critical account trait over time (e.g. track how the trait apiCallsMade changes over time)

Success Metrics will not be calculated retroactively. They will only be calculated from the date of creation moving forward.

How to Create a Success Metric

How To

How To Visual

Success Metric Available Data

Events

Events are the individual interactions users have with your product (as tracked by your analytics service) - e.g. Login, Button clicked, Purchase made. You'll usually have at least one Success Metric that uses events since they are the primary way to signal that a specific feature has been used by a user.

Because events happen hundreds to thousands of times a day, Success Metrics that use events are measured over a rolling timeframe (up to the last 30 days). This way, your event-based metrics can focus on the customer's recent usage of your product and how that trends over time. Keep in mind that Vitally already tracks all-time event totals for all your events by default.

User traits

You can also leverage specific details about each customer's users in your Success Metrics. This is commonly helpful if your analytics service already tracks some basic stats about your users - e.g. each user has a Total purchases made trait that tracks the total number of purchases ever made by a user in your product. In that case, you can use those stats to calculate metrics like the total and/or average number of purchases ever made for all users at each customer.

Account traits

Finally, you can also leverage account traits in your Success Metrics. There are two common use cases for doing so:

1. To normalize your Success Metric based on the customer's subscription with your business. For example, pretend that your product allowed each customer to upload up to 5, 10, or 20 videos every month based on their purchased plan. If your analytics service attached that video limit to customers as traits, you could easily measure how many of those 'pre-purchased' uploads each customer actually uses every month.

2. To track changes in an account trait over time. For example, say your engineers have already attached a Total Videos Uploaded trait to your customers. You could simply define a Success Metric that tracks the value of that trait as it changes. This way, you can easily see how that value trends over time for each account in Vitally.

Viewing & Reporting Success Metrics

Every Success Metric you create adds a new column to your accounts that you can view and report on (like all other account columns).

You'll also be able to use your Success Metrics when defining health scores and creating automated workflows with Playbook automations 🎉

One unique advantage to Success Metrics is the daily value of each account's Success Metric is tracked and cached in Vitally over time. This allows you to dynamically filter accounts (and run automated workflows) by a percentage increase or decrease in a Success Metric value over a dynamic timeframe.

You can also view this historical cache of Success Metric values for a specific account by clicking on the Success Metric in your Accounts list or navigating to the Trends tab of an account's profile.

Success Metric Examples

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.

A couple of different Success Metrics you can create are:

Active user percent at a customer
Percentage of licenses used per customer
Total airline tickets purchased per customer (last 30 days)
Percentage of a customer's users purchasing airline tickets
Average number of tickets purchased per a customer's users
Total dollar amount of tickets purchased per customer
Average ticket cost per customer
Average dollar amount spent on tickets per a customer's users
Unique travel destinations per customer
Percentage of a customer's users making any purchase
Total dollar amount ever spent on tickets by a customer's users

Expand to see the example Success Metrics

Hypothetical Success Metrics

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

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 😄. 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.