Success Metrics
Success Metrics are custom KPIs defined using the data you feed into Vitally and calculated for each of your accounts.
Last updated
Success Metrics are custom KPIs defined using the data you feed into Vitally and calculated for each of your accounts.
Last updated
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.
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.
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.
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.
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 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.
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
Q: How can I see Success Metrics for multiple Accounts? A: You can view individual Success Metrics while in an Account 360.
How To | How To Visual |
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How to create a Success Metric:
Navigate to your Settings (⚙️) by selecting your Account Logo on the top left and under Vitally Objects select Accounts or Organizations
Then select Success Metrics (or via Quick Jump Mac: ⌘ + j
Windows: Alt + j
).
Select Success Metrics
Name your Success Metric
Select which level of the hierarchy this Success Metric is for - Accounts or Organizations. You can not create a Success Metrics for Users
Select your Numerator
You can select between
Events
Calculate User level traits
Account traits
Depending on your selection you can apply event filters or a specific trait to calculate
Add in your denominator, this is optional (same options as numerator)
If you've select events, choose over how many days this metric would be calculated (can be max of 30 days)