By Ashamsa Mathew

For our Fall 2018 studio, we got the opportunity to explore the trends as mentioned in Designer 2025. Designer 2025 examines the changes in different areas such as technology, so it can address the possible trends that will change and affect the role of a designer. There are a total of 7 trends and we explored these trends as both a workshop leader and a participant. Both of the roles provided different insights.

Two workshops stood out to me in particular—‘Data portraits’ and ‘Data Economy.’ The workshops provided an authentic and insightful view of people, data and the design process. This also made me wonder how can designers grasp all this data? How can we use the data? Can we better the design process? Would we be taking away certain capabilities of a designer or empowering them? All these queries lead me to explore: ‘How can we as designers take advantage of the data economy to better inform and improve our design process?’

I started looking at different points in the design process where data can infuse useful insights into the design. This made me arrive at the initial process of design thinking. A lot of times we tend to assume certain characteristics to create our user persona and define their actions. However, if we built our initial user persona based on actual collected data instead of assumptions, we’d make more informed decisions and design choices. Rather than taking away a designer’s role, this instead aids the designer in what they are doing. Ultimately this would be a tool that assists designers in making well-informed choices at the beginning of their design process to generate more meaningful designs.

Personafy—A tool to assist designers

Mindy is a designer and is tasked with helping a local grocery store with promoting and encouraging people to eat healthily. To understand the user she is working with, she logs onto an interface which helps create a generic user profile based on collected data. The interface generates 3-4 data portraits of different kinds of users. She can then choose to isolate and look at the individual’s path through a store to gain insight into the user’s journey. Having acquired some quantitative data, Mindy can try to understand the qualitative aspects and the user experience of that journey. She can filter the conditions of the dataset such as only college kids, people who bought vegetables, people who did not buy fruits, and so on. She begins the first iteration of her design system, and after she has a method to test out, she applies her prototype to a sample area of the local story. Data is collected to that specifically designed area, and once she has enough data to reflect on, she can input the information into the interface, which then generates a user profile tailored to her intended user set. This helps her make informed design choices and understand how her users interact and experience her design, as well as if the design is accomplishing its intended goal.

The interface is dynamic and updates its database frequently to adapt to the ever-changing economy. The database does not record personal information unless uploaded by the designer and is kept private. If the system has the user’s permission to collect specific data such as profession and education level, it’s made available to the designer. The system gives the designer both a bird’s eye view as well as an in-depth view of the dataset.

Figure 1. Journey map. A designer can track the journey of a single random user to gain insight into an actual user. The journey map pins the various locations the user has stopped and records other information significant to the designer.

Figure 2. Data portrait. The data portrait paints a data-driven picture of a generic user of that particular grocery store based on the customizations initialized by the designer.

Figure 3. Customizing database. When we design a system, we tend to focus on certain aspects or elements of the system that would help us achieve our design goal. The designer can add relevant parameters.

Conclusion

We are always surrounded by and in interaction with technology in various forms; we ourselves become data points in the large data economy. With easy access to the internet and other resources, we as designers are accountable for an accurate representation of information and well-informed designs. Having access to a giant data pool also means newer innovations, smarter systems, and big data, so how does a designer make sense of this massive amount of data? Keeping these as motivators, Personafy is a tool that helps filter and synthesize data. Since the database is always being fed with input, it reflects the current standing in the economy so designers can make smarter and well-informed choices centered around their user. The system helps make the designer as well as the design adaptable, dynamic and reliable.

Ashamsa Mathew (MGD ‘20) is a Master of Graphic Design Candidate at North Carolina State University. She is interested in the integration of technology with design, mainly focusing on user experience.