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Is the value of your enterprise analytics SAAS or AI product not obvious through it’s UI/UX? Got the data and ML models right...but user adoption of your dashboards and UI isn’t what you hoped it would be?
While it is easier than ever to create AI and analytics solutions from a technology perspective, do you find as a founder or product leader that getting users to use and buyers to buy seems harder than it should be?
If you lead an internal enterprise data team, have you heard that a ”data product” approach can help—but you’re concerned it’s all hype?
My name is Brian T. O’Neill, and on Experiencing Data—one of the top 2% of podcasts in the world—I share the stories of leaders who are leveraging product and UX design to make SAAS analytics, AI applications, and internal data products indispensable to their customers. After all, you can’t create business value with data if the humans in the loop can’t or won’t use your solutions.
Every 2 weeks, I release interviews with experts and impressive people I’ve met who are doing interesting work at the intersection of enterprise software product management, UX design, AI and analytics—work that you need to hear about and from whom I hope you can borrow strategies.
I also occasionally record solo episodes on applying UI/UX design strategies to data products—so you and your team can unlock financial value by making your users’ and customers’ lives better.
Hashtag: #ExperiencingData.
JOIN MY INSIGHTS LIST FOR 1-PAGE EPISODE SUMMARIES, TRANSCRIPTS, AND FREE UX STRATEGY TIPS
https://designingforanalytics.com/ed
ABOUT THE HOST, BRIAN T. O’NEILL:
https://designingforanalytics.com/bio/
Episodes
5 days ago
5 days ago
On today's Promoted Episode of Experiencing Data, I’m talking with Lucas Thelosen, CEO of Gravity and creator of Orion, an AI analyst transforming how data teams work. Lucas was head of PS for Looker, and eventually became Head of Product for Google’s Data and AI Cloud prior to starting his own data product company. We dig into how his team built Orion, the challenge of keeping AI accurate and trustworthy when doing analytical work, and how they’re thinking about the balance of human control with automation when their product acts as a force multiplier for human analysts.
In addition to talking about the product, we also talk about how Gravity arrived at specific enough use cases for this technology that a market would be willing to pay for, and how they’re thinking about pricing in today’s more “outcomes-based” environment.
Incidentally, one thing I didn’t know when I first agreed to consider having Gravity and Lucas on my show was that Lucas has been a long-time proponent of data product management and operating with a product mindset. In this episode, he shares the “ah-hah” moment where things clicked for him around building data products in this manner. Lucas shares how pivotal this moment was for him, and how it helped accelerate his career from Looker to Google and now Gravity.
If you’re leading a data team, you’re a forward-thinking CDO, or you’re interested in commercializing your own analytics/AI product, my chat with Lucas should inspire you!
Highlights/ Skip to:
- Lucas’s breakthrough came when he embraced a data product management mindset (02:43)
- How Lucas thinks about Gravity as being the instrumentalists in an orchestra, conducted by the user (4:31)
- Finding product-market fit by solving for a common analytics pain point (8:11)
- Analytics product and dashboard adoption challenges: why dashboards die and thinking of analytics as changing the business gradually (22:25)
- What outcome-based pricing means for AI and analytics (32:08)
- The challenge of defining guardrails and ethics for AI-based analytics products [just in case somebody wants to “fudge the numbers”] (46:03)
- Lucas’ closing thoughts about what AI is unlocking for analysts and how to position your career for the future (48:35)
Special Bonus for DPLC Community Members
Are you a member of the Data Product Leadership Community? After our chat, I invited Lucas to come give a talk about his journey of moving from “data” to “product” and adopting a producty mindset for analytics and AI work. He was more than happy to oblige. Watch for this in late 2025/early 2026 on our monthly webinar and group discussion calendar.
Note: today’s episode is one of my rare Promoted Episodes. Please help support the show by visiting Gravity’s links below:
Quotes from Today’s Episode
“The whole point of data and analytics is to help the business evolve. When your reports make people ask new questions, that’s a win. If the conversations today sound different than they did three months ago, it means you’ve done your job, you’ve helped move the business forward.”
— Lucas
“Accuracy is everything. The moment you lose trust, the business, the use case, it's all over. Earning that trust back takes a long time, so we made accuracy our number one design pillar from day one.”
— Lucas
“Language models have changed the game in terms of scale. Suddenly, we’re facing all these new kinds of problems, not just in AI, but in the old-school software sense too. Things like privacy, scalability, and figuring out who’s responsible.”
— Brian
“Most people building analytics products have never been analysts, and that’s a huge disadvantage. If data doesn’t drive action, you’ve missed the mark. That’s why so many dashboards die quickly.”
— Lucas
“Re: collecting feedback so you know if your UX is good: I generally agree that qualitative feedback is the best place to start, not analytics [on your analytics!] Especially in UX, analytics measure usage aspects of the product, not the subject human experience. Experience is a collection of feelings and perceptions about how something went.”
— Brian
Links
- Gravity: https://www.bygravity.com
- LinkedIn: https://www.linkedin.com/in/thelosen/
- Email Lucas and team: hello@bygravity.com
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