The Power of Empathy: Michele Hansen on JTBD Research
Michele Hansen is an entrepreneur, author, and product manager. In 2014 she founded a SaaS company called Geocodio together with her husband. Michele loves talking to people so much she wrote a book on the topic: Deploy Empathy, one of our new favorites.
We were fortunate to have her as a guest on JTBD Untangled, where she discussed her approach to JTBD research, in particular connecting the problem space with the solution space. Jim caught up with Michele afterward to discuss her background and work with JTBD a little more. Read on to find out what she had to say.
JIM: Tell us a little about yourself and your background.
MICHELE: I started down this path as a project manager at a web development agency, then transitioned to being a product manager at a personal finance company, and eventually to co-founding a software company.
I love talking to people, and the more I talked to other entrepreneurs, the more I realized there was a need for JTBD and customer research resources for engineers and other people who don’t come from product or UX backgrounds. That’s what led to my book on customer interviewing, Deploy Empathy, which came out in 2021.
Personally, I grew up near Boston and moved to DC for school, and subsequently spent most of my adult life there… until I moved halfway across the globe to Denmark, where I live now.
I didn’t study anything remotely related to UX or JTBD — economics and international affairs — but both disciplines emphasize systems-level thinking and understanding underlying context and motivations in order to solve a problem. Human behavior in transactions, whether the role of incentives in economics, behavioral finance, or why someone buys a product, has long fascinated me.
JIM: How did you get into JTBD?
MICHELE: As a product manager, I had the tremendous fortune of being on a talented team filled with experienced UXers. They introduced me to JTBD and mentored me on how to conduct user research. This was about 8 years ago, and it was a turning point in my career.
Before that, I’d known two ways of building and improving a product: HiPPO, aka highest-paid-person’s-opinion (rarely worked), or looking at spreadsheets of data and guessing what would move the needle (also rarely worked). I’d conducted surveys and frequently listened in to customer support and sales calls, but it had never occurred to me to interview someone about their processes or experience with a product.
It was about a year into trying to read quantitative data tea leaves that I was introduced to JTBD, and realized that a spreadsheet of data will tell you what is happening, but it will never tell you why. Only people can tell you why. It was a revelation. Once I started using JTBD, things finally started to click.
Now JTBD is deeply embedded in the way I approach building/improving products and business strategy. My co-founder and I started our SaaS, Geocodio, as a side project, and I can confidently say it never would have gotten to the point of us being able to work full-time on it without JTBD.
JIM: Great to hear that getting introduced to JTBD was a turning point in your career. Can you share an example of a project you worked on where JTBD played a major role? What were you trying to accomplish and how did JTBD help you and your team?
Michele: When I worked in the personal finance space, we had one product related to planning for retirement. As part of revitalizing that product, we were given the green light to do a study on the retirement process, from active planning (50s) to fully retired (early 70s).
We’d had about a year of experience working with JTBD as a team at that point, so all of us knew the ropes and were able to really bring JTBD to life in how we conducted and analyzed our research. A couple of things stand out to me from that project:
First, how we used a wide variety of tools that were not necessarily products of the JTBD world and gave them a JTBD spin (like user journey maps and service maps, in addition to job maps). Looking at the same information through a variety of different lenses helped us get clarity on how our existing solutions did and didn’t relate to the overall job and sub-jobs, and where there were opportunities for new solutions.
For example, in our user journey map, each stage was broken out by the emotional, social, and functional sub-jobs.
Second, how JTBD gave us a vocabulary for communicating with the rest of the company on our findings: the idea that it was people’s goal to retire was something everyone intuitively understood, and we were able to use that as a jumping off-point to introduce other ideas of the framework and talk about the importance of sub-jobs, and use that to facilitate discussions about struggles and product opportunities.
JTBD made it much easier to communicate with people who were unfamiliar or even skeptical of user research, as it makes the process and results structured. Third, how enjoyable it is, and how productive it is, when the whole team is speaking the same language.
Everyone was submerged in the framework and that made our process-from early planning to running the study to analyzing to communicating to running product experiments — so much more productive. And because we used JTBD, our research was more illuminating and our prototypes more quickly successful, which fed the team momentum. JTBD made the process more rigorous and predictable, but also more fun.
Lastly, for me personally, it was when I truly understood the power — both positive and negative — of using empathy in interviews. I’d been doing user research for maybe two years at that point, yet the topics of the interviews weren’t deeply emotional: picking stocks for a portfolio, for example.
It wasn’t until I was doing interviews for this project and having people tell me how they consulted actuarial tables to see how long they’d live and how long their spouse might live to see if there would be enough money left over for their spouse if they died first, or the painful process of re-self actualizing as a person after retiring, or how they were deeply afraid of becoming homeless in retirement, that I realized how powerful, and dangerous, interviewing techniques can be.
I wasn’t prepared for the idea that I might get someone talking about a topic and lead them to the point of tears or revealing their deepest fears.
JIM: That is powerful. What cautions or words of advice would give people using empathy in interviews?
MICHELE: I also learned to have boundaries around when I use those techniques. I talked about in my book how one day I found myself chatting with the cashier at the grocery store, and before I knew it they were telling me about the company’s various acquisitions over the years and how their retirement plans had changed and how they were worried how they would string together income from several different sources in retirement.
Reflecting on it as I made my way home, I realized it was inappropriate for me to pull that level of information out of someone without them explicitly opting into it. I just hadn’t fully realized how powerful of a tool empathy is, and how I needed to be careful with it. I always cared about our users and the people I talked to, yet this project left me with an even greater sense of care and responsibility for how I handle interview subjects and what I do with what they tell me.
Before, when I thought about ethics in interviewing, I mostly thought about the sharing of their information with other people, rather than setting boundaries on their behalf on what they should tell me. I didn’t have appropriate boundaries on how I used those techniques in my daily life, either. I now have a greater ability to calibrate my use of empathy and only go as deep as a situation genuinely requires.
JIM: Thanks for those stories. With the advent of AI, folks are now talking about skipping the interviews completely, at least within the field of JTBD. What’s your take on that? I’d love to hear your general thoughts on AI and research as well.
MICHELE: I think AI is exciting for its potential to help automate time-intensive, low-value uses of time in the overall user research process, such as interview transcription and doing a first pass at pulling trends out of a survey.
Using AI to minimize time-consuming steps makes research more accessible to smaller and less well-resourced teams. As a JTBD practitioner, my ears always perk up when I hear about steps of any process that are repetitive, laboriously manual, time-consuming, or expensive, and AI has a role to play in our own user research processes by shrinking the time, effort, and expense of those steps.
Yet, AI cannot replace all pieces of the process. Interviews are the meat of JTBD research and there is no substitute for listening to a person talk about their experience and the particulars of their context that lead them to have a specific JTBD, the ways they’ve tried to accomplish it, the struggles they’ve had, and so forth.
I’ve asked ChatGPT to imagine itself in various scenarios, and it is overly-eager to build a narrative for its imaginary decision-making in different scenarios. Humans do this too, but the difference is that in human interviews, we can cut through the imagined narrative to find the true, messier process. It is in that mess that opportunities lie.
We’ve all experienced interviews where we walked in hoping to learn one thing and ended up learning something entirely different, and more valuable, that we’d never even considered could be part of the picture. A lot of what we’re trying to uncover relates to the particulars of someone’s process that may have never been articulated and thus could not have entered AI training data.
When we interview someone, we’re trying to get their genuine experience, and that is the opposite of artificial.
With that said, I think it makes sense to incorporate new technologies into the process where it makes sense. For example, I’m excited about the potential of using VR in engendering empathy — in the future, it could be a helpful tool in sharing research across the organization to stakeholders who weren’t personally present during interviews.
JIM: What are some of the impacts you’ve seen from using JTBD? Got any good case stories to share?
The biggest impact in my own work has been the sense of direction and focus that JTBD brings. Before I started using JTBD, I felt like I was making product decisions that were educated and data-informed — but ultimately guesses.
Understanding the direction people are moving in and why allows me as a product leader to zoom out on the entire process and find opportunities in a way that is just so much clearer than without JTBD.
To me, a Job Canvas and especially the Job Steps are the prime hunting ground for opportunities to solve business problems, like growing revenue, reducing churn, or building new products. It’s the difference between walking into a grocery store knowing what you’ve got in the fridge and a mental list of favorite recipes and going in hungry on a whim without any real sense of direction except frantic energy. More than anything, JTBD to me means calm.
For my own business, one of the key ways we apply the results of JTBD is by looking at job steps. My company is very niche — we do location data enrichment. When we launched, which was over 10 years ago now, we only offered conversion of addresses to latitude/longitude (so a computer can read them and ex. put them on a map).
We started to learn from our customers that while many people had the use case we’d had in mind — making a map — many other people only needed the coordinates because it was a doorway to other pieces of information about an address, like Census data or political districts. We then learned that in some cases, people needed to use many different services — sometimes over 5 — in order to even get to the point where they had the piece of data that was useful to them. That meant a lot of complexity in their process to compile and normalize that data, nevermind dealing with different companies with different terms, pricing, and processes.
We realized that we had an opportunity by providing that data all in one place and significantly reducing the amount of time, hassle, and expense for people. So from the early days, it became a core focus for us to eliminate or reduce Job Steps, and it’s still our primary product strategy: understand the Job Steps people are going through, understand whether there are other adjacent Job Steps that are solveable by us and play into existing operational strengths, and figure out if it is competitively advantageous for us to do so (market size, how well that market is served, market behavior, etc).
In addition to giving me clarity about product direction and opportunities, it’s also deeply satisfying to understand the steps that go into someone’s Target Job and to know that we’re making a difference in their work lives. I think many of us want to feel at the end of the day like the work we’re doing is helping other people, and to me, there’s nothing quite as motivating or professionally satisfying as knowing that we’re helping make someone’s day just a little less frustrating or time-consuming.
JIM: Thanks, Michele!
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Be sure to check out Michele’s book, Deploy Empathy:
