Google’s HEART framework in UX
Measuring UX is not always easy, and Google’s HEART framework can help us overcome this challenge. It was designed to help UX teams focus on specific aspects of the user experience they want to improve, as well as identify concrete goals and user experience metrics to measure success.
It was developed by Kerry Rodden, Hilary Hutchinson and Xin Fu, who were part of Google’s research team.
What is Google’s HEART framework?
When we work on a small scale, measuring user experience is relatively straightforward. We can talk to users and understand their opinions. But if we are working on larger projects it can be very complicated. To address this, Google proposed a research framework to enable the listening process to be done in a systematised way.
The HEART framework is a useful framework because it is simple and easy to understand. This model is designed for large projects, but can also be implemented in smaller projects (the methods used for data collection will simply vary).
Google’s HEART framework is based on a two-axis matrix: the HEART metrics and the Goals-Signals-Metrics process.
Google HEART framework metrics
The HEART framework is a set of user-centric metrics, which is divided into 5 different categories:
- Happiness
- Engagement
- Adoption
- Retention
- Task success
UX projects are always unique, and each has its own requirements. This means that not all projects will require all metrics. Depending on what is needed, you will need to choose the right combination of metrics.
For example, the engagement metric will only make sense in some situations. If we think of a digital product for use at work (a tool for managing company accounts, for example), this metric will be of limited value, because users do not choose to use it, but are required to use it as part of their job. Users who will use the product will not always be engaged with it. In this case, assessing engagement is not the most relevant metric.
Happiness
This metric is a way of measuring attitude or satisfaction when using the product. In large-scale projects, one way to measure happiness is through satisfaction surveys or the Net Promoter Score.
As with all metrics, a snapshot in time is not enough to make decisions. Long-term observation of metrics will provide better data for project decision-making.
Engagement
Engagement is used to understand how much a user interacts with a product, of their own free will. It measures the level of user involvement, or how much time they spend using the digital product.
As mentioned above, it can be a poor metric for corporate digital products, because there is no optional element to its use. If you have to do a job, you have to use the product.
To measure this category you can look at regularity of use, intensity of use, or overall level of interaction over a period of time. The correct metrics will vary from product to product.
Adoption
Adoption is the number of new users over a given period of time, who become regular users (after the trial or welcome process).
Associated metrics can be new subscriptions or, in an app, upgrades to the latest version.
Note that much of the adoption is not due to UX, but to sales and marketing activity. Investment in marketing and sales can overcome UX issues, but only for a short period of time. In the long term, a poor UX is likely to discourage new users as they read reviews and talk to friends, colleagues, etc. about the product.
Retention
Retention measures the ability to keep existing users for x amount of time. This could be an indefinite period of time for products with long-term utility.
Benchmark metrics are recurring purchases or the renewal rate of a service’s payment plan.
Depending on the project, we can look at a specific time scale to help us visualise when users stop using the product or service. A week, a month, a quarter or a year are perfectly reasonable intervals, as well as any other interval relevant to the business.
Task success
The “task success” metric can be broken down into more subtle components. With this metric we can measure aspects such as the time spent completing a given task or the percentage of successful completion of a task.
To quantify this metric, usability testing can be done (remotely or on-site), and we can measure successful search results or the creation of a new profile.
The Goals-Signals-Metrics Process
The second part of the evaluation matrix corresponds to the Goals-Signals-Metrics process.
By following this process we will be able to visualize and align the project objectives with the different members of the team.
Goals
The first step is to identify what goals we want to achieve in the sections of the HEART framework we are interested in.
Defining the goals will help to get all team members on the same page and working towards a common goal. Some questions we can ask ourselves are:
- Is it more important to attract new users or to increase the participation of existing users?
- What tasks do we want new users to complete?
Signals
Each objective has related user actions or signals. By assigning the objectives to these actions we will be able to know if the project is on track.
For example, users renewing their subscriptions means that the retention rate is good.
Metrics
The last step is to decide which metrics to use to monitor signals.
It is very easy to create a very long list of potential metrics, but it is important to keep that list to only those metrics that can help make UX decisions.
Depending on the project to be developed, we will have to take into account some categories of the HEART framework or others, and this will help us to measure the quality of the UX. On the other hand, with the Goals-Signals-Metrics process we will be able to measure the goals of the project or digital product.
If you are interested in learning UX don’t miss our UX Learn trainings (in Spanish):
This is a translation of the following article published in our corporate website:
