You don’t have to do research. If you’re an artist or a chef or a writer, you produce what is inside you to inspire or delight your audience. People buy your product for these feelings.* But if you’re an organization with products and services designed to support people, such as an insurance company, a library, or a data management company, it’s a big risk to operate like an artist. Assumptions will lead you astray, and your competition will be the people who are delighted. Developing ideas based on superficial, quickly-generated understanding of how people are thinking is not wise. But neither is doing so much research that you delay production of your ideas. So, when should you do this kind of deep research?
Many organizations incorporate understanding people as a part of an overall cycle, only to run into trouble. When they try to exert the least effort for the greatest clarity in deeply understanding people, it doesn’t actually fit into the process. There’s not enough time for it. Teams value the knowledge but are constrained to make do with shortcuts, which sometimes lead to sloppy pseudo-science. So here’s how to fix it: allow time for deep understanding by severing deep understanding from any cycle and letting it run separately, with a cadence that makes sense for what you want to know and when you need to know it. This means little breaks in product development now and then where your team gets into people’s minds. (Or it could mean a parallel team doing this research, but that runs the risk of the knowledge not really being absorbed by the people who need it most.) Deep understanding is not a one-time effort. There is not a big report at the end. You add to your understanding continuously, but in small, skillfully selected scopes of exploration. You can add to the data whenever you encounter gray areas about the people you support and what they are trying to get done.
Understanding people comes in a lot of flavors. All of them are useful at different points of product management. Some of them can be run quickly, but not others. Let me clarify.
The most common definition of understanding people is making sure your solution works for people. It’s A/B testing, usability testing, user interviews, or analytics. It occurs after the designs have taken some sort of form.
Becoming much more common these days is validating an idea that your team has — making sure the concept has legs before spending any time on development. It’s doing just enough research and validating concepts as frequently as possible. It occurs after ideas have surfaced, but before they’ve taken design form.
Even less common is understanding people before idea generation. It’s trying to get inside people’s minds to see how they achieve their larger intentions and purposes without reference to your organization. The goal is to allow for later idea creation that is not constrained by existing services or organizational philosophies. It occurs before the ideas come up.
Here’s an example, in reverse chronological order, with questions that are typically asked. The questions in italics are questions that require deep understanding and a separate process to give yourself time to truly understand.
After the design has taken form: How well does our gym coach app work for people? Does this feature work better in this configuration or that configuration? What about writing the content this way or that way? Why aren’t people responding as we expected? Why are our customers behaving the way our quantitative data depicts?
After the idea has surfaced: Is our idea of a gym coach app going to be helpful? Can customers help us come up with features? Did we look at this from all angles? Can our idea be tailored to support different audiences in different, nuanced ways?
Before the ideas come up: What went through people’s minds as they have worked to stay generally fit, to lose weight, to recover from an injury, to train for an event as a newbie or a repeater or a champ, to build muscle? What are the patterns of reasoning? What kinds of different thinking-style segments do people fall into? Which of those segments or patterns do we want to support now?Later? Can we provide deeper support or maintenance of a person’s intents? Are there opportunities to (re)define our offerings so people naturally flock to us because of how well we support their thinking? How can we compete based on intrinsic value in people’s lives instead of simply monetary value? Are we leaving brilliant ideas undiscovered?
The italics in all three sections above indicate questions that organizations have trouble answering with confidence. These questions require deep understanding of what goes through people’s minds. These are the questions that cannot be answered speedily.
The connection between your organization’s offerings and deep understanding is support. How does your organization help people achieve their intent or purpose? (Instead of support, it could be “persuasion” or “behavior change,” but those are topics for another day.) Which thinking-styles do you support better than others? Digital products are past the pioneer phase now. So successful organizations get ahead by providing support that is not minimal but nuanced and varied, paying attention to many details and perspectives. It’s more than just decorating interactions with wry phrases designed to make people grin — which ultimately fail for a much larger percentage of users than you suspect. It’s about providing different answers for different thinking-styles, or choosing which thinking-styles to help with.
Let me define “deep understanding” again. It’s what people are thinking and how they are reacting — not about tasks and goals, but as they pursue larger intents and purposes. It’s not “book a flight” or “take a trip,” but “rescue the client relationship.” People achieve that larger purpose an a number of different ways, following a number of different philosophies. If you are asking questions like those in italics above, you can collect and curate this knowledge in a depiction of the reasoning-patterns (mental model diagrams) and the thinking-styles (behavioral audience segments). And you can consciously and clearly decide to execute in support of certain patterns.
One of the other things about deep understanding that makes it different from other flavors of research is that it doesn’t grow stale. It’s valid for years or decades. It’s about people’s human thinking, not about technology or interactions with services. Human thinking doesn’t evolve all that quickly. (E.g. deciding to attend a performance.) You could have asked your great grandparents and gotten answers that would still be valid today. This research can be added to over time, cumulatively. Hence your team can add little chunks to it over time, when certain questions come up.
The value emerges after you re-frame the way you think about the problem as if your organization does not exist. When you come back to reality after this little exploration, your deeper understanding influences the way you think about the solutions. You can spin quickly for several months in the design and development cycle based on the deep understanding you gained.
Organizations need all kinds of levels of understanding people. It’s good practice to know which kind of understanding to reach for in which situation. When you have questions like those in italics, above, you reach for deep understanding, whether it’s pre-idea, post-idea, or post-design. But more importantly, you don’t reach for deep understanding when your questions are more typical of the development process. These other explorations can more easily fit into the spinning cycle.
If you think of all the possible research/understanding tools at your disposal, the reasons-for-use fall into the intersection of evaluative, generative, quantitative, and qualitative study.
You can think of the boxes that result from these intersections as toolboxes, in a way. Depending on what you want to achieve, you reach for a tool in one of these boxes. Mature practices reach into each of these boxes, over and over.
But in the diagram above, I want to bring attention to the fact that even mature practices spend most of their energy focused on thinking post-idea and post-design. This arena is referred to as the solution-space in product management. There’s another layer, called the problem-space. That’s pre-idea.
The italic questions above are all answered with qualitative studies, and they scatter across generative & evaluative, solution-space & problem-space according to the nature of the answers desired.
Pick the right tool for your intention. Use lots of tools, and make sure you have a balance of knowledge from each of the boxes. Most of your research goals will fit into your existing lean processes reasonably. If you try to squeeze deep understanding into your existing cycles, you’ll try to push it too fast, and poor information will result. That poor information is a risky foundation for product decisions, and more often than not it will mean you will have to go back and re-do something. So I recommend running the studies you do to gain deep understanding separately from your lean process. Chop them off; run them at a separate cadence.
Research for deep understanding is for when you want to look outside your organization to see what the future can hold. Indi is available to help.
*You could be an edge case, like a news agencies such as NPR or The Daily Telegraph, or you cater to fashion like Urban Outfitters or Chanel, you are balanced between creating for delight and creating in support. In some parts of your work, your inspiration for delighting customers comes from within; in other parts, you seek to support people by helping them seem knowledgeable, confident, and well-put-together. Research these latter types of topics.