Google’s HEART method — what, how & the perks

Adonay Lizardo
Published in
6 min readApr 30, 2020


The objective of this article is that you know all the essentials of this Google UX method and, most importantly, how to apply it to any project you are dealing with — be it an application or a website.

Let’s start from the beginning

There are many ways to measure changes made to an application or website to see if they work or not.

The “problem” is that although they serve to put figures to the changes and make statistics, in some cases they are too generic: they are related to the user experience, but there are occasions when it is difficult to directly relate a % of bounce low with all that the UX implies, which after all is a person.

To try to solve this gap, Google developed its own framework / method, called HEART (Happiness, Engagement, Adoption, Retention, Task Success).

Applying the HEART research method for Xara Cloud

Benefits of HEART method:

  • Easy & Cheap — That makes communicating the reasons for selecting it easy across teams.
  • Scalable — While the framework may be designed for large projects; there’s nothing to stop it being implemented on smaller projects either
  • Established — The technique has been used extensively for over 10 years.
  • It involves users — Studies provide insight into users interactions with your website/app functionalities.
  • It Provides a good foundation — HEART method provides a robust foundation to understand how users behaved during a certain amount of time and if the performance of your product is performing as expected.
  • It Provides good insight — Compliance (or not) with the objectives, metrics and signals set will be a source of information and useful data to make improvement decisions.

Demerits of HEART Method:

  • The 5 metrics are not quantifiable — For this reason, we must use the goals, signals and metrics to convert it to figures.
  • Varied results — This is the complex part, because the response to these three factors varies depending on whether we judge the application or web as a whole or value only a specific feature. It is not a process that can be automated, so it must be defined specifically on each occasion.
  • Beware of false positivesMarketing or sales efforts during that study period can mess up your results a bit. It can happen in the launch of a massive platform upgrade, where money is invested in advertising campaigns and therefore traffic goes through the roof. In these cases, HEART must be accompanied with other methodologies to compare and validate results.

How to choose the Metrics

Leaving aside the chance that the acronym ends up forming the word HEART, I explain below what each letter is about.

We measure adoption rates by: Most clicked buttons in the Editor and Click rates in Editor.

H for Happiness

Through surveys -the most common method-, the attitude of each user is evaluated. For example, satisfaction, perceived ease of use, Net-Promoter Score, etc. It is usually carried out, therefore, through surveys on the website itself, appraisal in app stores, by email, etc.

E for Engagement

Try to measure user participation. For example, counting the frequency with which you use the application or the web, the intensity or depth of the interaction in a given period of time, etc. This translates into the number of visits received per user per week or the number of photos or videos uploaded to the application, likes given or messages sent, etc.

A for Adoption

In this case, it is a matter of measuring how many new users are earned, how many are obtained every X days, percentage of purchases made by new users, etc. Adoption is used to see to what extent new users start using the application or the web.

R for Retention

It is the rate of return of current users. In other words, how many active users there are in a given period of time compared to another period (for example, comparing the current month with the previous one).

We could also understand retention as the number that represents the time that passes from when a user downloads or registers an application until they leave it forever. That is, the time he spends with us until it stops using us.

T for Task success

In this case, we also include traditional measures of UX in relation to behavior, such as efficiency (time to complete a task), effectiveness (percentage of tasks completed) and error rate. This category is best suited for product areas that require specific tasks, such as uploading photos, updating a profile.

How to choose Goals, signals and metrics

Gut feeling is good but data-driven UX design is better. Here is where things start getting complex (and interesting).

Those are some of the tools we use to applying this methodology

Define the goals

Usually we have a tendency to create a document with a long list of metrics … which in the end is relegated in a drawer because day-to-day does not allow us to be on top of so many variables.

For this reason it is essential to define the objective for each “letter” of the model, which is what will allow defining the appropriate metric. That is, it will allow us to go towards a target and improve a specific figure, avoiding shooting ten targets at the same time.

Define the signals

The signals are the “indicators” that will allow us to recognize if that defined objective is being met or not. For example, if in Engagement the objective is for the user to discover and read more content, the signal will be the time they spend on the web or reading each article.

Actually this aspect serves to not to lose the north and confuse the objective. It may seem silly, but with day-to-day it is easy to “forget” what defined what.

Defining the metrics

It’s about the concrete metric. In the previous example, it would be the time each user spends on the web and the average of each day / week / month.


Measuring user experience on a small scale is relatively easy. It’s what user experience designers do on a daily basis. You can observe users, talk to them, ask them questions, etc. and get rapid feedback. HEART framework is a great technique for UX research both small and large-scale projects.

More and more, UX plays a key role for product teams around the globe and this is a great way to approach the analysis.

If you want to take this further with other UX methods such as usability testing our user interviews it can help you to find out some functional info about users to get new projects up and running.

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All the points that I’ve mentioned are as per my understanding and experience, so feel free to drop in your comments. Positive criticism is always appreciated. 🤘🏻💎.



Adonay Lizardo
Editor for

Ayudo a Startups, emprendimientos y empresas a diseñar experiencias digitales memorables. Entusiasta de la meditación.