Successful product design requires more than a brilliant idea and a team of talented implementers. It also requires a deep understanding of who the users are, and how they experience the product.
No matter how experienced the design team is or how many successful products they've created and launched, there is never a substitute for user data. The reason for this is simple:
Designers are not users.
Without data, there is no way to concretely validate your assumptions to ensure that you're creating designs that meet the needs of your users.
No matter how experienced a designer is, the only way to create a product or service that truly fits the needs of the intended users is by using data that’s obtained from observing and communicating with your users directly.
- What is Data-Driven Design and Why Does It Matter to UX?
- Types of Data: Quantitative and Qualitative
- How to Understand Your Data to Learn What Matters to Users
- How to Present Your Data to Win Stakeholders
- Key Takeaways
What is Data-Driven Design and Why Does It Matter to UX?
Data-driven design is the practice of basing your design decisions on data rather than intuition or personal preference.
It requires an ongoing commitment and understanding of the value of this data, to the point where the entire design process is structured around obtaining and analyzing research. Without data, user experience design does not exist; the end result is limited to the design team's perceptions and experiences.
When you begin your design journey, you can start to form data-driven design habits by embracing user research and testing (collecting the data), and using the insights gleaned to arrive at your design decisions.
As you advance in your career, data mastery will play an increasing role in how you formulate your design strategy and emerge as a leader in your field.
Types of Data: Quantitative and Qualitative
Data-driven UX design uses two main types of data: qualitative and quantitative.
Quantitative Data Collection Sources
Quantitative data is objective data that can be measured through concrete numbers or values. However, the meaning behind this data is open to interpretation. Quantitative data collection sources include:
- Analytics data, from sources like Google Analytics or Mixpanel, shows page views, clicks and bounce rates.
- Usability test results that measure how long it takes for users to complete a task or find a specific piece of information.
- Heat maps which show exactly where users click on your website or product.
- A/B testing which tests single variants to see which performs better.
- Multivariate testing, which uses multiple variants to test a hypotheses.
- Usage analytics which comes from actual user interactions with a product or service. This data can give information about how users navigate through a website, what features they use the most, and how long they stay on a page.
Qualitative Data Collection Sources
Unlike quantitative data, qualitative data is subjective and cannot be measured objectively. However, qualitative data offers perspective and a richer insight into the why behind user behavior.
You can gather qualitative data through UX research methods such as:
- User Interviews, where users share responses to a predetermined set of questions.
- Focus groups, where a group of users talk about a product or experience in a moderated conversational setting.
- Surveys, where users leave written feedback on their product experience and opinions.
- User feedback, which is gathered from surveys, interviews, focus groups, and other research methods. This type of data tells us about users' needs and preferences.
While any kind of data is valuable, collecting a combination of quantitative and qualitative data can help create a more complete understanding of the greater context behind a user's actions or opinions.
Read more: AI Tools to Streamline & Enhance the User Research Process