Generative UX research is “next level” research. It moves us beyond tactical inquiries (like we see with usability testing) and towards a more strategic user understanding. It enables us to direct the way a company innovates, and it’s a challenging method to master.
The best way to learn generative research is by doing it—which begs the question, “But how do I start?” Or for more advanced practitioners, “How do I ‘practice’ better?”
This guide will equip you with everything you need to start strategically and practice well.
Many names, one objective: what is generative research, anyway?
Discovery research, problem-space research, foundational research, in-depth interviews, exploratory research, customer interviews. You’ll hear generative research go by dozens of names. Regardless of what the methodology gets called at your org, the goal will be the same.
Generative research is defined as research that deeply “generates” an understanding of who your customers are (as humans, not as users), and what they experience in their everyday lives. It’s a style of interviewing that allows us to dig into a person’s identity beyond their screen, and beyond their interaction with our product.
And sure. We’re still trying to understand how a product or service impacts these folks. But knowing their everyday lives should impact the way we build our product or service.
I can’t stress the importance of this concept enough. To prove my point, I’ll give you an example of a time when my team thought we’d asked all the right questions.
Why generative/exploratory research is essential
The product we were working on was relatively simple: it provided e-commerce companies with a social media repository. They could use it to aggregate the posts they were tagged in, and then repurpose those posts for their own, authentic, user-generated marketing efforts.
So first we asked companies how we could make the product better, and what features we could add to make their lives easier. We were product-centric, not user-centric; we acted as if the user revolved around our product, rather than the other way around. With that mentality, we missed a lot about their pain points and needs.
Finally, once we started doing generative research, we learned about our users’ lives and workflows. We found that they’re trying to put reports together early in the morning for overseas clients. We saw that some of them wanted to use their commutes to go through some of the social media in the repository.
Some of our users were trying to look good in front of their bosses during stressful presentations, so as to potentially get a raise or a promotion. Many of them had families and were looking to be more efficient so they could get home earlier to see children and partners. Armed with this knowledge, we could develop features far past our initial, product-centric scope, which helped our users so much more than we could have imagined.
This information was invaluable, but it would’ve been impossible to come by if we asked about features. Generative research, instead, gets people to tell important stories about their lives that go far beyond a product or a service. It gives you rich information about their overarching goals, needs, motivations, and the why behind their behaviors. And that why behind someone’s actions will give you the information you need to positively impact their life.
The value of generative/exploratory research
Generative research tells us why people are doing things and what they are thinking in a given moment. It takes us out of the product and into the lives of the people we are trying to help. We can easily get stuck in a box when we think about a product, and, with that, we can become quite short-sighted. We only think about things within the product, instead of the greater impact.
Generative research helps us break those boxes in order to come up with a truly delightful and helpful solution to a user’s problems. Instead of starting with a solution, and trying to work backward, you are actually entering from the problem-space.
This style of interviewing allows us to uncover the deeper motivations and actions behind why users are doing certain things. It’s really easy to look at quantitative data and see what people are doing on your website or app, but it is literally impossible to know why they are doing those things through this data. This is where the qualitative bit of user research comes in, and where generative research really shines through.
By taking the time and effort to conduct these sessions, we are able to get valuable information that paints a picture better than any standalone persona or customer journey map. This enables us to do a few very important things:
Better prioritize work
Have confidence when deciding on new features or product areas
Understand and empathize with the users’ situations
Build a product roadmap and vision
Another wonderful thing about generative research is that you can really do it at any time. I prefer to run a study at the beginning of a product’s life, or the start of a company, rather than further down the line. However, you may not always have a say in your company’s research timeline.
For example, if you get hired as a user researcher at a company that is already established, you might hope there has been some foundational research conducted—while also mentally preparing yourself to fight for generative research projects.
Although the value of generative research may be clear to some, it can take more time and effort than other methodologies, such as usability testing.