The design of new products needs to be based and some kind of idea or starting point that teams can base their work on. This starting point can be based on heuristics and guidelines as well as previous versions of a product or existing designs. If you want to start your process in a more user-centered way, you can also use user-related data, information, and knowledge as the starting point that informs your design choices. If you chose this approach you’re doing data-driven design–with the end goal of helping users of the product you’re developing to understand the purpose of the product and how it works. That way, you can make sure the product fits users preferences, expectations, goals, and needs. As a result, the user experience of your product will most likely be a pleasant, seamless one.
Reasons for data-driven design
There are always multiple stakeholders who influence the design and development process of products as well as their usability and UX. Naturally, there will be different expectations about the product’s features. While your initial impulse might be pleasing higher-ups and investors by designing the product in the way they expect it to be, your first priority should always be the product’s end-user. Users who have a efficient, smooth experience while using the product, are much more likely to continue using it or to recommend it to colleagues and friends. As a result, you can expect an increase in sales which should satisfy most other stakeholders besides your users.
Figuring out, whether your team is moving in the right direction and really making process towards reaching your goal also becomes easier when you use data. On top of that, data helps you understand pain points your users encounter during their journey, new patterns and trends that arise as well as opportunities for the future. Observing users’ behavior helps you to get to know them more intimately and to understand the reasons they have for certain behavior. Research will provide you with insights that are based on facts and will help you make informed decisions to improve your design.
Start your data-driven design process
We have elaborated this in a previous blog post: you are very likely to already own a certain amount of user-related data even if you don’t think you do. While data is often gathered specifically for the purpose of improving your design using surveys or user tests, you can as well employ data that results from website analytics or is stored in your existing database. Website visitors and users leave behind a trail of information, which you can use to sharpen your knowledge of your target group and create a more compelling design by making it more tailored. Start this process by gathering existing data as well as website analytics and improve personas you might already have by analyzing said data.
These personas can, for example, be used to choose participants for user tests and surveys which in turn results in more data. That way you can add more depth to your data sets and iterate your products, improving their design. Existing data can also be analyzed with the goal of uncovering gaps in your knowledge that need to be closed. Once you identified missing information, try systematically to close them by conducting appropriate research. You can also combine quantitative and qualitative data. Combining all these different kinds of data is certainly a lot of work but well worth it as it will give you enriched, deeper insights into your users’ thought processes.
Benefits of data-driven design
Quantitative data which is used to measure users behavior using scales and numbers and qualitative data, which gives you an idea of the reasons behind users actions, each have their strengths and weaknesses. If you want to build truly great products that have a compelling UX, you will most likely have to employ both types of research. First ideas and the basis of design are often rooted in instinct. Data will help you to grasp why things are the way they are. They will also help you to justify your decisions in case they are questioned by stakeholders. On top of that basing your design on facts you know about your user base, you will eliminate difficulties in predicting what your users need or want. The more different designers and users are, the more difficult this becomes. Even though the assumptions that users don’t really know what they need exists, oftentimes users actually know very well what they expect a product to do. Sometimes there are already similar products to what you plan to design available to your target group. In this case, users who already used these products will most likely have certain expectations for your product. So do user testing and let users tell or show you what they want and need.
Connecting data analysis and facts with creativity may sound counter-intuitive. However, insights concerning your users can help you and your team to generate new ideas and move in a new direction past best practices. Use insights to challenge existing assumptions and gain courage (and back-up) to ignore or modify best practices. Guidelines as well as design rules are useful depending on the circumstances and are also based on facts. Still is you follow them blindly you risk designing a product that is very average and hard to distinguish from comparable products. Design easier to use, more effective products by starting with the user and designing the most pleasant user experience you possibly can. Problems can be solved more efficiently if you are informed about users’ wants and needs. In case you need to justify or explain why you deviated from common guidelines, employ the data you used to come to that decision.
Combine user research and data analysis with the work of designers and UX professionals to eliminate the majority of the guesswork during product design. Design guidelines, heuristics, and established principles are used when designers or developers don’t know where to start their work. While they are widely accepted and used, as soon as your target group becomes very specific these guides are not a whole lot better than simply guessing. If you want to give your design process a clear direction try to understand users motivations, behavioral patterns, and context.
If you are unable to conduct specific surveys or user tests, use data you already have to get
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