How to Choose the Right UX
Metrics for Your Product

Created by Digital Telepathy in collaboration with Google Ventures

Based on the article by Kerry Rodden

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Google’s HEART Framework helps measure the quality of user experience.

List of Goals

You can apply HEART to a specific feature
or a whole product.

 
 
 
 
 

Happiness

Measures of user attitudes, often collected via survey.

For Example

  • Satisfaction
  • Perceived ease of use
  • Net-promoter score

Adoption

Gaining new users of a product or feature.

For Example

  • Upgrades to the latest version
  • New subscriptions created
  • Purchases made by new users

Retention

The rate at which existing users are returning.

For Example

  • Number of active users remaining present over time
  • Renewal rate or failure to retain (churn)
  • Repeat purchases

Task Success

Efficiency, effectiveness, and error rate.

For Example

  • Search result success
  • Time to upload a photo
  • Profile creation complete

Choose one or two categories in the
HEART framework that are the focus of
your product or project.

 
 
 
 
 
 

But how do you figure out which
metrics to implement and track?

It starts with goals.

The Goals Signals Metrics process
facilitates the identification of
meaningful metrics you'll actually use.

 
 
 
 
 

Goals

Identifying clear goals will help choose the right metrics to help you measure progress.

You may not realize that different members of your team have different ideas about the goals of your project. This process provides an opportunity to build consensus about where you're headed.

A common pitfall is to define your goals in terms of your existing metrics - "well, our goal is to increase traffic to our site."

Yes, everyone wants to do that, but how will the user experience help? Are you interested in increasing the engagement of existing users or in attracting new users?

Signals

Map your goals to lower-level signals.

There are usually a large number of potentially useful signals for a particular goal. Once you have generated some promising candidates, you may need to pause and do some research or analysis to choose.

If you're already collecting potentially useful signals, you can analyze the data you have and try to understand which signals seem to be the best predictors of the associated goal.

First, how easy or difficult is each signal to track? Is your product instrumented to log the relevant actions, or could it be? Second, you should choose signals you expect to be sensitive to changes in your design.

Metrics

Refine those signals into metrics you'll track over time or use in A/B testing.

The specifics depend a lot on your particular infrastructure. But, as in the previous step, there may be many possible metrics you could create from a given signal.

You'll need to do some analysis of the data you've already collected to decide what's most appropriate.

Avoid the temptation to add "interesting stats" to your list. Will you actually use these numbers to help you make a decision? Do you really need to track them over time, or is a current snapshot sufficient? Stay focused on the metrics that are closely related to your goals to avoid unnecessary implementation effort and dashboard clutter.

The Goals Signals Metrics process
should lead to a natural prioritization
of the various metrics.

 
 
 

It helps to have metrics that reflect
the quality of the user experience,
and that map to your main goals.

This worksheet can help*

*Remember, you only need to include the HEART categories relevant to your product.

Happiness Engagement Adoption Retention Task Success
Goals Signals Metrics