Know About Data-Driven Product Design
                     What is Data-Driven Product Design? 
 
 
The Product Design Process and Data 
Product design is a constant process of iteration. No product is developed off the first design, 
making collaboration and teamwork crucial to successfully navigating the design process. What 
turns a design team into a data-driven team is when analytics is used to boost team-driven 
systems and workflows. A data-driven design process doesn't seek to replace teamwork with 
data, rather it uses data to supplement and improve existing capabilities. 
Data within Design 
Implementing data analytics into product design is not a new concept. However, the difficulties 
and obstacles associated with this are often underestimated and misunderstood. Adding new 
technologies or platforms without a corresponding emphasis on qualitative judgements can 
lead to designers overlooking product flaws if, for example, those issues do not have a 
corresponding effect on quantitative data. 
In data-driven design processes, data cannot supplant qualitative judgements. Qualitative 
processes and workflows, such as visiting and speaking directly with customers; provides 
valuable insights that cannot be substituted with data visualizations or analytical reporting. 
It can also be helpful to think of data as being more than simply reactive analysis. Data can be 
used to generate ideas for the design process. For example, using analytics to understand 
customer concerns or needs can help teams scope out and anticipate customer frustrations and 
pain points before the product goes to market. 
Data is at its most valuable when it is used proactively to shape the customer experience. 
Anticipating customer needs, wants and concerns can be difficult to perform on scale. Teams 
can only meet and speak to a limited number of customers each day. However, when customer 
concerns are recorded and compared through analytics, wider trends can be discovered. 
Data is also invaluable in helping designers specify when updates are necessary to a product 
line. Many updates require the tracking of users through workflows to be accurate. This 
tracking and measurement of users would be near impossible without the help of product 
analytics. The impact of updates can then also be measured quantitatively, giving designers 
insight into the expected and actual effectiveness of product updates. This data can also give 
designers a view into whether updates should be rolled out across entire product lines or 
specific models. 
Your Data-Driven Team 
Of course, when using data, it is important to keep in mind that culture and fit are equally 
important to design teams. A company culture that respects arguments supported by data, 
seeks to include data as evidence and respects quantitative trends will find much more success 
with product analytics than one that doesn't. Organizations that also encourage 
experimentation and collaboration between teams will find more success with implementing 
data-driven processes and workflows in their teams.  
This of course comes back to the original ideal that data-driven design processes can only 
augment human capabilities and culture, not replace them. Design is uniquely collaborative, 
and team cultures that allow for this will be much better at implementing data-driven strategies 
than teams with poor culture. Data and analytics cannot replace a team with great culture, 
processes and fit.