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Data Analysis in Design Overview

Data analysis (DA), often combined with artificial intelligence (AI), has found critical applications in the field of design. Whether the subject is medicine, construction, or the user experience of a social networking site, the single most crucial question for design is “what does the customer want”? By tapping into the vast amounts of data surrounding customer behavior and underlying processes, a researcher can find new answers to this question. These answers, in turn, will help guide his or her design process towards improving the design of existing products or creating entirely new ones.

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Previously, customer sentiments on a product had to be obtained through surveys and analyzed by hand. Today, similar data can be obtained from customer reviews, then collated and analyzed algorithmically without significant loss of accuracy compared to human analysis (Ireland & Liu, 2018). In online applications from online shops to social networking and news websites, user experience (UX) metrics can be collected directly by tracking user behavior such as clicking links or duration of stay on a page (Ishan, 2020). This data, when analyzed, allows a designer to identify any shortcomings or opportunities for improvement and act on them. In this way, data analysis allows to receive immediate and active feedback on user experience and quickly act to improve it.

As the Internet of things (IoT) expands, adding more sensor-equipped devices connected to the Internet, the amount of data on previously poorly researched user behavior becomes available. Smart homes allow new insights into people’s daily lives and inform the design of more comfortable and efficient living spaces and appliances (Gerencer, 2019). This is one example of data collection and analysis allowing to design real objects and processes that ultimately improve people’s lives.


Gerencer, T. (2019). How telemetry powers the Internet of things (iot). Web.

Ireland, R., & Liu, A. (2018). Application of data analytics for product design: Sentiment analysis of online product reviews. CIRP Journal of Manufacturing Science and Technology.

Ishan (2020). Data-driven design: Providing optimal user experience. Web.

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