If you’re a designer, engineer, or product manager building software today, you likely interact with users a lot. You probably run interviews with your customers to identify their wants and needs. You probably collect and analyze qualitative and quantitative user feedback on your product. And you probably conduct usability sessions in order to build useful, usable, and delightful software.
The machine learning team at HubSpot recently published a paper which we presented at the Uncertainty in Deep Learning Workshop at the Uncertainty in Artificial Intelligence conference. In this paper, we outlined how we’re using machine learning to help our customers do better A/B testing in HubSpot. This technology is now available in HubSpot’s Lead Flows tool, and we’ll soon roll it out to many other areas of the product. In this post, we’ll explain how the technology works and how it will help our users accomplish A/B testing with less effort and higher returns.
UX Research seems to be one of those careers: everybody in it is a life-long learner. It’s a great fit for the naturally curious, and for people with a strong investigative bent. I’m lucky to be part of a UX research team at HubSpot whose members strive to collaborate, share lessons learned, and teach each other different ways of working so we can all grow. And as we all remember what it was like to be starting out in the field, we also love to mentor junior researchers as they learn and mature in their career.
At HubSpot, we’re working to build a more diverse and inclusive place to work. We want to make sure that HubSpot is the kind of place where everyone can do their best work. We also want to make sure that our software — which thousands of companies use in their own workplaces — fosters an inclusive environment for our customers, too.
It takes a village to build a product. Not literally, of course; but the sentiment is the same. You need many different people in many different roles in order to get a successful product off the ground. Without everyone’s individual skills and perspectives — their special piece of the puzzle — product decisions can easily fall prey to bias and missed opportunities.
HubSpot relies heavily on this village model for virtually all of our product teams. For each team, there’s a core group of people who do most of the heavy lifting when it comes to building their product. Engineers bring their deep understanding of constraints and technical tradeoffs. Designers use their deep knowledge of the user, her experience, and design standards across the product. And product managers contribute their broad and varied insights about the business. This core team is supported by a number of other people who are integral to a product’s success: UX researchers, UX writers, expert support reps, and, of course, product analysts.
As our team has grown, we’ve reached a point where tribal knowledge just doesn’t get transmitted as easily as it used to. For much of this tribal knowledge — like why half our infrastructure team recently Photoshopped lasers onto their eyes in their Slack pictures — it’s not a big deal if not everyone's in on the joke. But when it comes to our team’s values — the very principles that shape how we work, and why — well, we want everyone to be on the inside.
At our engineering leadership offsite last month, we realized that as we scale, we need to share our engineering values — our most important tribal knowledge of all — more plainly, more publicly, and more often. While much of our value system gets transmitted by osmosis during everyday interactions between people and teams, we recognized that it was time for more explicit reinforcement and articulation. If we aren’t deliberate about exposing new hires to these principles early and consistently, as time goes on, we risk eventually diluting (and possibly losing) these important and hard-won values altogether — values that have shaped the team and the company that we are today.
