Measuring Product Design Success Using the HEART Framework
In designing a product, we want the goals we plan to achieve. But we cannot see it based on a personal point of view or subjectivity because the success rate of a product is seen based on data or numbers.
It is like between Product Design and Abstract Art. Abstract art has a value that only the painter or a few people know, and sometimes even we are confused about the meaning of the art. While Product Design has a clear value in the eyes of everyone, be it positive or negative.
But the big question is, how do you measure the success of a Product Design?
Before that, let's get acquainted with the HEART Framework🤍
— What is HEART anyway?
HEART is a Google-made framework used to measure a matrix or measure a design's success.
HEART stands for Happiness, Engagement, Adoption, Retention, and Task Success.
"There are so many. Do I have to use them all?!" - Of course not.
There is no set framework, so we don't have to use all of them and adjust them to our needs.
#H — Happiness😄
Happiness can be defined as user satisfaction
— For example, we can see through user ratings or feedback on an application, whether it's through Playstore, Appstore, etc.
#E — Engagement😍
Engagement can be described by user intensity in using the product.
— A case in point is when we order food through an app, how often do we order food using the app or even open it just because it's annoying *lol.
#A — Adoption🤩
The implementation of new features can illustrate this.
— An easy example is when we create a new feature in the application, we can calculate it from how many registered users use it.
#R — Retention😤
Retention can be measured by how we retain users.
— "What is to be maintained?" We can maintain the number of users who have registered to use our app again or stay with our app.
#T — Task Success🥳
With all the features we have created, we can measure the success rate of a feature.
— When a user has a problem, we provide a feature to solve it. Then we can calculate how many users have used the feature so that their problem is solved.
Last but not least, I want to remind you that if we make a product, it must refer to data, not just subjective assumptions, because a product must be validated whether the product is needed by users or just our speculation.