Today’s article is about “Google Framework In Measuring Large Scale User Experience,” where we will discuss how the tool works in measuring user experience.
We will also cover the following topics:
The Google HEART Framework was designed by Google’s research team, led by Kerry Rodden, Hilary Hutchinson, and Xin Fu.
The idea behind this is simple: to deliver a series of user-centered metrics on a large scale. And these metrics are useful for decision-making in your product development process.
In user experience research, you probably know that it is relatively easy to measure the metrics in a small-scale user experience. You observe your users, talk to them, ask them several questions, and get their feedback.
The Google research team explained that while it is common to adapt the practice of measuring a small-scale user experience on a large-scale mode through different automation methods, it does not have a framework set in place.
And thus, they introduced the HEART framework, which explicitly targets large scale user experience measurements using methodologies that are different from measuring small-scale user experience research.
The HEART Metrics
There are five components in the HEART Framework, and these are:
Happiness is a metric used to measure the level of attitude or satisfaction. One way of measuring happiness on a large scale is by user survey.
Most of the time, the results of the level of happiness in user experience are not long-term. For example, a change in your product feature or interface resulted in an initial drop of happiness metric does not mean that the change has a long-term effect on your users.
Thus, it is essential to record time as enough basis to make the right decisions. Also, long-term observation is another way to provide better log user data regarding decisions during product development.
Engagement is a metric of how much a user willingly interacts with your product. In terms of measuring enterprise systems, this metric is not advised because there is no optional element in terms of usage patterns. Whether the employee loves the tool or not, they still need to work and get the job done.
This metric requires examining and measuring the regularity of use, the intensity of use, and the overall interaction level over time.
Of course, these are not the standard metrics for measuring user engagement. The right metrics vary from product to product. For example, in a weather app, you will rarely see user engagement compared to other apps that most require it.
Adoption is a metric defined as the number of users over a specific time frame (how many users in a specific period of time). This is a metric of how your business is doing overall. Many argue that this metric is more of a customer experience measure rather than a user experience measure.
There is a strong case for an argument about this as not much of adoption is not on user experience but instead on sales and marketing activities.
And it is possible that for a short period, investing in marketing and sales can resolve a low number in adoption metric. However, in the long term, a poor user experience in this metric can result in users discouraging new users from using your product through customer reviews.
Always be cautious in measuring adoption metrics, and we recommend that you share insightful and dynamic thinking with your sales and marketing teams to be able to properly make decisions to help you maintain a long-term good user experience.
Retention is a metric that keeps your existing users for a certain amount of time. The amount of time is indefinite for this metric, especially for products with long-term utility.
We suggest that you look for more ways to define the retention metric that works well for your product or service. For example, you can look for a scale where the dropout service is most seen to resolve UX-related issues that lead to those dropouts. You can set and define your own intervals to a week, a month, or a year. Any reasonable time that is relevant to your business.
When it comes to rolling out new products, the adoption and retention metrics are critical. If there is an instance that the product is not going well and fast as predicted, it would be reasonable to assume that there will likely be a plateau in which these metrics deliver good results.
Task success can be broken down into two subtle components that may include traditional behavioral metrics: One is the time spent on any given task (can the process be improved?), and two is the percentage of the task success of specific functions once it has begun (like checkout or registration processes).
How to use the HEART Framework
Step 1: Goal setting
Setting your goals signals metrics from the start is an excellent strategy to get every team member on the same page. You can ask questions like, “Is it important to attract new users or increase engagement for existing active users?” or “What are the tasks that need to be completed by the users?”
The goals will be different every time. The goals signals metrics of a product or medium app from another company may be different from your own goals, even though your product or medium app is similar to that of the company.
Another important thing to remember when setting up goals is to set up no more than three goals.
The HEART framework can be a tool that is simple to use for large scale user experience research. However, juggling with more than three goals signals metrics simultaneously also provides you with more than a dozen meaningful metrics to analyze.
Step 2: Define the signals
You also need to know that every goal has a related user action. Thus, it is essential to map your objectives to these actions to be on the right track.
A vital guide question for this step is: What behaviors or user attitudes would show that your goal has been met or failed?
For example, A user entering a keyword or phrase in the search box but not clicking the search button may indicate failed UX metrics or insights.
Another example would be that reading the website content or browsing the website pages can indicate higher engagement.
Step 3: Pick the right metrics.
The last step is to get the distill goals signals metrics into traceable metrics that you can easily monitor in real-time.
For Happiness metric, you may check out the Net Promoter Score for tracking results.
There are so many potential metrics that you can generate for your product or service. And thus, it is better to keep your list short and manageable by only choosing the right metrics to help you may good UX decisions.
The advantages of using the HEART Framework
There are so many advantages to using the HEART, but here are some of the popular ones:
Helps in getting valuable trends, insights, and business intelligence
The HEART framework can track and measure the same user experience from multiple angles (such as happiness, retention, etc.), and thus, it is helpful to a company in identifying essential patterns that may improve one metric or may weaken another.
Like for example, if the company focuses more on increasing user adoption, this can impact the product’s happiness score. With the insights you get from using the HEART framework, your team can easily adjust how you build or market your product.
Helps in strategizing on where to focus more work
User experience research can be overwhelming that sometimes, with the massive amounts of data, the UX team finds it hard to start forces their work on.
With the Google HEART framework, the UX team can quickly draw their attention and energy to areas of the user experience where they think have the most significant impact on the product.
With the HEART framework, the team can generate valuable insights that show which of the five metrics have the most significant and consistent measure progress leading to an increase in revenue.
For example, if the Google HEART framework revealed that investing in retention can add more bottom line than investing in user engagement, the UX team will know how to place more of its resources on the new product.
Back to you
Congratulations! You have finished this how-to article on the Google HEART framework. Now it is your turn to experiment with this framework. You may use this article as your starter reference for applying the HEART framework to your product. Good luck!
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