Data-Driven Design–Designing with Data in a User-Centric Way

think moto
5 August 2022

We talked to Marie Bossecker, Senior Experience Strategist at think moto, about Data-driven Design. She has many years of experience in combining data, strategy and design in such a way that they form the basis for development processes for digital products and services. We asked Marie what data-driven design actually is, how data-based design and creativity are connected, and how innovation gains quality through user data.

Data-driven design is radically user-centric and derives from design thinking. The first step, even before the strategy and design process begins, is an extensive collection of real user data that reflects the current behavior of the user group. Together with further data collection during the process, they form the basis for the development of new approaches in strategy and design.

“Data-driven design means making design decisions based on prior research and data analysis.”

The term data encompasses both the results from qualitative research, such as interviews, and quantitative research, such as surveys or tracking data.

What is the Data-driven Design process?

As with many design approaches, there is no clear process template. The steps presented here are a framework that can be used as is or modified slightly. As a structural basis, the 5 steps of Design Thinking serve: Empathize, Define, Ideate, Design and Test.

1. Data collection & analysis

Data can be collected using various methods, e.g., qualitative user interviews or quantitative data collection. Tools that anonymously query or record user behavior, such as in-page surveys, heat and click maps, or eye tracking, can be used for this purpose.

Data analysis is the task of the strategists. They interpret the data and filter out the problematic interfaces. Many modern tools for data analysis can help to identify conspicuous features and hierarchies that promote or negatively influence the performance of a website.

2. Definition

The task now is to react to the findings and assumptions made. This phase is accompanied by extensive research and, if necessary, user tests to re-examine the assumptions. There are many inclinations in the market that can affect user behavior. For example, the pandemic. User behavior has changed extremely as a result. These external influences and trends are highlighted and analyzed in the definition phase.

“Does a better conversion rate mean we’ve had success, or are there perhaps other movements in the market or in the target group that are influencing this result?”

3. Strategy

In this stage of research, a strategy/concept is developed based on the previous steps, which addresses the identified problems and includes possible solutions. As a rule, several approaches are developed here, which must prove themselves in the course of the further process or are just discarded.

4. Design & Implement

Based on the strategy, conceptual and design measures result, which are implemented by the designers. These are then implemented in the existing website. But the job is not done after that.

5. Test

After implementation, a test phase is carried out again to check how successful a measure was. The data obtained can then be used in turn to draw lessons and develop a revised strategy. This cycle is also known as “customer journey optimization”.

What role do strategists play in the data-driven design process, and how do they differentiate themselves from data analysts?

In quantitative methods, data analysts are primarily responsible for enabling data collection, i.e., creating an interface between the platform and the analysis tool, storing the data, and making it available to strategists in accessible dashboards. Interfaces, such as Google Analytics, hotjar or VWO, make the collection and transmission of data possible in the first place. In order to better evaluate the generated data, it is translated into dashboards and presented in an understandable way using data visualization. The strategists gain access to the data and can now evaluate it. Their task is to analyze and interpret the collected data, define measures, accompanied by extensive research, and then develop a strategy.

In qualitative methods of data collection, for example interviews or focus groups, strategists can be involved from the beginning. They develop the study, define aims and set the framework. After data collection, they then also evaluate the data.

What is the added value from combining strategy and data analysis in the design process?

With the flood of digital offerings, those who know their users best and create the best experience for them will prevail. The short attention span of users has made it all the more important to present relevant content in the most accessible way possible. The better the experience is tailored to the user and their needs, the longer their stay and the higher the likelihood of a “conversion,” such as a purchase or download.

It is almost impossible for designers today to include all the needs of potential user groups in design decisions. Some use the website very frequently, others only drop by occasionally. There are digitally affine personalities and those who need more assistance. That’s why it’s important for designers to draw on previous, data-based research. These show the current, real-world behavior of active user groups.

“You can’t know as a designer what your users really do or need without prior, data-based research. That’s where the clear difference lies between having some opinion and having some knowledge.”

Where does our Branded Interactions design process link to the Data-driven Design approach?

Data analysis can be well integrated in all phases of the branded interactions design process. It depends on the project and the industry of the customer how intensively the analysis of user data can be applied. Data collection is particularly helpful on websites with high traffic, where many users come together, such as in a large e-commerce store. Chatbots and their interfaces also provide a good basis for increasing performance through data in the long term. Qualitative data collection, on the other hand, can also support pure branding projects and MVBs and help to better understand the user group from the beginning through interviews and other research methods.

“Especially in the first two phases, Discovery and Define, data-driven strategy can be linked to the Branded Interactions design process. In Phase 5, Distribute, likewise, as the goal then is to evolve what has been implemented.”

Doesn’t creative freedom get lost if you always refer to data?

Real user data should not be a restriction on design freedom, but should serve as a support in the development of new design approaches. The data shows designers which approaches are already working well and which are not working at all. This allows them to focus on the essential pain points and create solutions where they are really needed. There are no limits to creativity itself.

Continuous analysis of user behavior helps us to optimize what we already have and adapt it to users in the best possible way. In order to develop new, innovative approaches, you have to keep questioning your previous knowledge to see what might work even better. Innovative design approaches can also be improved again and again through user testing and research.

What challenges do trends and technologies from the fields of tracking and data analysis bring for the combination of data and design?

In addition to external factors, such as pandemics, climate change or sustainability, current trends play a decisive role in how we behave online. For example, video content currently works much better than static content, as platforms like TikTok or Instagram guide. The need to be treated as an individual also has an impact on what we demand from our online experiences.

 “When it’s my birthday, I expect a fat voucher from the brand I’ve already left hundreds of euros with.”

The line between personalizing content and manipulating buyers can be very thin. Every click and every text written reveals more about what we like and even how we feel right now. In parallel to the real personality, we also have a virtual one, which analytics tools build from our behavior, our data, and then feed us the content that best suits us.

“I believe that in the future, the line between manipulation and personalization will become narrower. The question is, after all, where do we draw the line? What is exploitation, what is convenience? As designers, we have a supporting responsibility to position ourselves.”

Want to learn more about the design process at think moto? You can read all about it in the book Branded Interactions by our founders. Also check out our project portfolio on to learn more about our work.