The Google HEART framework is a powerful framework to ensure you take into consideration every aspect of the user journey
In this post, we will dig into the Google HEART framework: a simple way to ensure you take into consideration every aspect of the user journey. This post is from a set of articles about choosing the right metrics when working as a product manager.
When you think about a great product manager (PM), you might picture Steve Jobs and see him as a visionary. He defeats the status quo and follows his intuitions to set up his vision.
In practice, all PMs are not Steve Jobs, so following your gut feeling is good, but making data-driven decisions is even better. Having a framework to decide which metrics would best guide your product in the right path is critical. That’s where the Google HEART framework comes in to play.
What you will find in this article:

1. What HEART stands for: the five categories of metrics

HEART is a metric framework, popularized by Kerry Rodden, a UX researcher at Google Ventures. It is a simple way to ensure you are thinking about every aspect of the user journey and the way a user sees your product.
HEART stands for:
Happiness: How happy is your user? For example, if we look at telecom companies (your usual internet provider), they usually have thousands of customers, even if those customers are not happy.
Engagement: How engaged is your user in the short term?
Adoption: How many interested users have tried your product?
Retention: How many users do you retain long term?
Task success: How successful are you at allowing users to perform the most valuable task?
Now, looking at the order of each metric, it doesn’t seem right: You would have difficulty getting happiness without adoption. The HEART acronym is easy to remember, but the more correct order of the cycle is:
I guess Google Ventures thought it would be easier to market a HEART framework than an ATERH framework. :p

2. Goals, signals and metrics are the three factors you need to consider

The next stage of the HEART metric is called the GSM process:
The “Goals Signals Metrics” process facilitates the identification of meaningful metrics you’ll use (dtelepathy.com).
Note: For all the examples, I preferred to follow the logical user cycle (adoption, task success, engagement, retention and, finally, happiness) instead of following the order of the HEART acronym.
2.1 Goals: What do you want to happen?
Do we want to maximize or minimize a specific behavior or result? As an example, for an offline retail shop, your goal might be to reduce the time the customer waits at the cashier and maximize the number of items he or she purchases.
2.2 Signals: What is the thing we need to measure to get closer to the goal?
Signals are actions that show a goal that has been met, or responses that relate to success or failure. For example, for Twitter, if a user starts writing and editing a tweet but closes it before publishing, it’s a signal of failure for task success.
We can explore several examples of signals for each category for an e-commerce app:
Adoption
Task success
Engagement
Retention
Happiness
2.3 Metrics: How will signals manifest as metrics?
Metrics is a number to look at to know whether the product is going well. Once you identified your signals, you want to connect to metrics that are trackable and measurable.
If we break down the signals identified before into metrics, we would get:
Adoption
Task success
Engagement
Retention
Happiness
3. Why the HEART framework is so powerful
Here are several reasons the HEART framework is so useful in your day job as a product manager:
  1. You can use the HEART metrics framework for anything: a company, a feature, a product.
  2. You can use the HEART framework for reporting purposes. Have the metrics in a dashboard. Display those numbers for your boss and executives to see. It would bring transparency and save you a lot of time preventing unnecessary update meetings.
  3. You don’t need to use all the metrics from the HEART framework to be useful. You can list all relevant metrics, start tracking a couple, then only work on improving a few. You can always start small.
  4. Signal helps you define how to track metrics. You can use the signals as a guide to what you need to do to process and track the metrics. You can then share those signals with your data engineer team, so they know what they need to do to set up the correct analytics.
Congratulations if you made it this far! This article is just a beginner intro into the HEART framework. Now it’s your turn to play with this framework, and apply it to your product.
Have fun :)