Data is everywhere. Living in the age of information and communication and the Internet means living in the age of data. Advances in computer science and programming languages have made research, statistics, collection and classification, and most importantly data analysis easier and faster. One might think that making it easier to collect data and analyze it is only good news for scientific research and academic researchers.
But it is not. Data is also the basis of business decisions and strategies. SEO experts, digital marketers, and even product designers use data to make decisions and evaluate their plans. The importance of statistics for SEO experts or digital marketers is somewhat clear, but what does data have to do with user interface design, user experience or product design?
“Data Driven Design or DDD is where data reaches product design and UI/UX.”
What is data-driven design? Why should ui/ux design be data driven? Why should a ui/ux designer have the skills to use data in his design? Why is it said that product design (basically any product and not just digital products) should be data-driven? What are the advantages of data-driven design in user interface design and user experience?
Every day that passes, the role of data in product design increases and this relationship becomes closer and more important. In this article, based on the opinion of reference sites in ui/ux, I discuss the important role of data in interface design and user experience and answer the questions posed above.
Table of Contents
Data-oriented design in UI/UX design
If we want to divide ui/ux design into several parts and list its basic concepts, quantitative and qualitative research and types of tests will definitely have a place in that list. There is also an important reason: user interface and user experience design is done for the user (human). The goal is to solve his needs and problems. In design, human interaction with the product and the usefulness and enjoyment of this interaction are the first words. In a word, design should be human-centered.
How should the ui/ux designer, the design team, the product owner and the business understand what the product user (that human) wants? What does it need? And what problems does the product have to solve? The design team finds the answers to those questions by using quantitative and qualitative research and various methods that exist for each. It is with this research that the designer understands the user and his behaviors better.
The result obtained from the research is nothing but a collection of data, quantitative and qualitative data. Quantitative research data is numerical. In data-driven design, the type of data that is important and used is quantitative and numerical data. Numbers are more reliable and telling.
Let me give an example. The design team of a software launches a new version of it. In a research about the use of this software, they find that more than 60% of users spend a lot of time doing some things. They research more about this number and come to the conclusion that the tooltips ruined the UI design of some parts.
I think the following quote sums up the importance of numerical data very well:
“What’s measured gets managed. Numbers have an important story to tell.”
What is Data Driven Design?
Data-driven design can be defined in several ways. In the most concise form, data-driven design means design based on quantitative data analysis. In the process of designing and improving the quality of any product (especially digital products, such as web and application), the ui/ux designer has to make several decisions.
In data-driven design, the designer makes decisions based on quantitative data and numbers. That is, if the designer is stuck in a dilemma and the results obtained from the qualitative research lead him to one choice and the quantitative data lead him to another choice, he gives more weight to the quantitative data and makes a decision.
Of course, the mistake should not be made that when the designer chooses data-driven design, he leaves out qualitative data altogether. It is not like that at all. The main argument is that quantitative data becomes the most important basis for decision-making in data-driven design. But the point here is that qualitative data are still effective and should be considered along with quantitative data.
What are the advantages of data-oriented design in UI/UX design?
In response to this question, another question should also be answered: basically, why are data, including quantitative data, decisive in product design?
- In general, data helps the design team to know the main users (consumers) of the product, their needs and problems;
- Quantitative data helps the design team easily test their designs and ideas to see which ones worked best;
- When there is a reliable benchmark (numbers) to evaluate different solutions, the hands of the design team are open to consider creative and innovative ways and find new solutions to product problems and shortcomings;
- Quantitative data, because they are not abstract and concrete, show well what the priorities of the design team should be;
- When the design team is more creative and implements ideas supported by quantitative data, it can be expected that a more efficient product will be produced for the user;
- When from the beginning of the design process, all decisions are made based on numbers, it means that everything goes in a certain direction and there will be fewer mistakes. As a result, time and costs of the team and product production will be saved.
When should a designer use data-driven design?
This question cannot be answered definitively. This is a decision that the design team of each product must make based on various factors. The UI/UX designer of a site may come to the conclusion that the site design should be based on quantitative research and data from the very beginning. The app design team may have several ideas for improving the app, and because they don’t know which ideas users like the most, they decide to try them. In the end, the idea that can get a higher percentage of satisfaction wins.
A very good example of the latter is Instagram. You must have noticed that before adding something to it, Instagram activates it for a group of users to see what feedback it gets and how many users use it. Instagram has done the same to measure the option of liking stories. I don’t have this option yet, but some of my friends can like stories. Of course, in this case, Instagram may pay attention to a set of quantitative and qualitative data to make the final decision.
How should a UI/UX designer use quantitative data?
Before I talk about these questions, how is data-driven design done? And what steps should the designer go through to have a data-driven design? I must point out a very important point. A prerequisite for data-driven design is quantitative research in user experience. The design team must first get the data right. The first step is this, and the second step is using data. I will not discuss quantitative research in this article because it is covered in detail in the article on quantitative research in UX + introduction to its methods.
In the first step, it is important that the design team obtain reliable, useful, bias-free and error-free data. The design team must determine from what sources (internal or external) they need to obtain data. It may be necessary to get statistics and figures from other departments and teams, even business management. Therefore, the first step (especially in large businesses) may be very challenging for the UI/UX designer and the design team.
We come to the second step. The principle in the second step is that:
“The designer must understand which data he needs and how to use each data in his design.”
In order for the designer to understand how and in what direction to use the data, he must:
1. Consider overall business goals and user needs
The product must sell. Businesses ultimately produce products for this purpose. So the design team should consider to produce a product that the user wants and definitely buys. For this reason, statistics and data should be used that show the user’s needs and problems well.
2. Analyze and review the data deeply
Perhaps it can be said that the most important work of the design team is the analysis and review of the screened data. Statistics and figures should be analyzed in depth as much as possible so that the different aspects of an issue and a behavior can be clearly defined. The design team needs to hear all the words from the data.
3. Look for user behavior patterns in the data
User behavior has hidden and obvious patterns. The ui/ux designer should look for user behavior patterns in the data. Different data should be compared. If needed, it should be researched again and data collected.
4. Visualize the analysis results (Data Visualization)
Finally, the data needed and the data the team wants to make decisions on should be visualized. It is easier to explain the data from figures, diagrams and charts. The product design team should also be responsible for business management. Maybe the new decision will require more funding. So the design team should also include the senior business managers with their decision.