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Are you responsible for creating business impact with data products, SAAS analytics solutions, dashboards or generative AI/ML applications? Do you believe one of the biggest challenges with monetizing data products is navigating the humans in the loop—from stakeholders to users? Do you believe that a product-driven approach coupled with solid UX design is critical to ensuring that analytics and ML solutions even get used? My name is Brian T. O’Neill, and on Experiencing Data, I offer you a designer’s perspective on why simply developing ML models, dashboards, and apps—outputs—aren’t enough to drive meaningful user and business outcomes with data. Through solo episodes and interviews with data product management leaders, CDAOs, VCs, and designers, I explore how teams are integrating product-oriented methodologies and UX design to ensure that data products get used in the last mile. After all, you can’t create business value if the humans in the loop won’t use your “solution.” Whether you work in product at a B2B / SAAS analytics company, or you build internal data products for a traditional enterprise, join me as I dig into what’s working—and what isn’t. Hashtag: #ExperiencingData. PODCAST HOMEPAGE: For 1-page summaries and full text transcripts, join my Insights mailing list on the podcast homepage: https://designingforanalytics.com/ed ABOUT THE HOST, BRIAN T. O’NEILL: https://designingforanalytics.com/bio/
Episodes
Tuesday Jul 26, 2022
Tuesday Jul 26, 2022
Today I chat with Chad Sanderson, Head of Product for Convoy’s data platform. I begin by having Chad explain why he calls himself a “data UX champion” and what inspired his interest in UX. Coming from a non-UX background, Chad explains how he came to develop a strategy for addressing the UX pain points at Convoy—a digital freight network. They “use technology to make freight more efficient, reducing costs for some of the nation’s largest brands, increasing earnings for carriers, and eliminating carbon emissions from our planet.” We also get into the metrics of success that Convoy uses to measure UX and why Chad is so heavily focused on user workflow when making the platform user-centered.
Later, Chad shares his definition of a data product, and how his experience with building software products has overlapped with data products. He also shares what he thinks is different about creating data products vs. traditional software products. Chad then explains Convoy’s approach to prototyping and the value of partnering with users in the design process. We wrap up by discussing how UX work gets accomplished on Chad’s team, given it doesn’t include any titled UX professionals.
Highlights:
- Chad explains how he became a data UX champion and what prompted him to care about UX (1:23)
- Chad talks about his strategy for beginning to address the UX issues at Convoy (4:42)
- How Convoy measures UX improvement (9:19)
- Chad talks about troubleshooting user workflows and it’s relevance to design (15:28)
- Chad explains what Convoy is and the makeup of his data platform team (21:00)
- What is a data product? Chad gives his definition and the similarities and differences between building software versus data products (23:21)
- Chad talks about using low fidelity work and prototypes to optimize solutions and resources in the long run (27:49)
- We talk about the value of partnering with users in the design process (30:37)
- Chad talks about the distribution of UX labor on his team (32:15)
Quotes from Today’s Episode
Re: user research: "The best content that you get from people is when they are really thinking about what to say next; you sort of get into a free-flowing exchange of ideas. So it’s important to find the topic where someone can just talk at length without really filtering themselves. And I find a good place to start with that is to just talk about their problems. What are the painful things that you’ve experienced in data in the last month or in the last week?" - Chad
Re: UX research: "I often recommend asking users to show you something they were working on recently, particularly when they were having a problem accomplishing their goal. It’s a really good way to surface UX issues because the frustration is probably fresh." - Brian
Re: user feedback, “One of the really great pieces of advice that I got is, if you’re getting a lot of negative feedback, this is actually a sign that people care. And if people care about what you’ve built, then it’s better than overbuilding from the beginning.” - Chad
“What we found [in our research around workflow], though, sometimes counterintuitively, is that the steps that are the easiest and simplest for a customer to do that I think most people would look at and say, ‘Okay, it’s pretty low ROI to invest in some automated solution or a product in this space,’ are sometimes the most important things that you can [address in your data product] because of the impacts that it has downstream.” - Chad
Re: user feedback, “The amazing thing about building data products, and I guess any internal products is that 100% of your customers sit ten feet away from you. [...] When you can talk to 100% of [your users], you are truly going to understand [...] every single persona. And that is tremendously effective for creating compelling narratives about why we need to build a particular thing.” - Chad
“If we can get people to really believe that this data product is going to solve the problem, then usually, we like to turn those people into advocates and evangelists within the company, and part of their job is to go out and convince other people about why this thing can solve the problem.” - Chad
Links:
- Convoy: https://convoy.com/
- Chad on LinkedIn: https://www.linkedin.com/in/chad-sanderson/
- Chad’s Data Products newsletter: https://dataproducts.substack.com
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